Publications: Journal articles, conference papers and theses from department members

2016
1. Ahmad M, Helms V, Kalinina OV, Lengauer T: The Role of Conformational Changes in Molecular Recognition. The Journal of Physical Chemistry B 2016, 120.
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@article{AhmadJPhysChem2016, TITLE = {The Role of Conformational Changes in Molecular Recognition}, AUTHOR = {Ahmad, Mazen and Helms, Volkhard and Kalinina, Olga V. and Lengauer, Thomas}, LANGUAGE = {eng}, ISSN = {1520-6106}, DOI = {10.1021/acs.jpcb.5b11593}, PUBLISHER = {American Chemical Society}, ADDRESS = {Washington, D.C.}, YEAR = {2016}, DATE = {2016}, JOURNAL = {The Journal of Physical Chemistry B}, VOLUME = {120}, NUMBER = {9}, PAGES = {2138--2144}, }
Endnote
%0 Journal Article %A Ahmad, Mazen %A Helms, Volkhard %A Kalinina, Olga V. %A Lengauer, Thomas %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T The Role of Conformational Changes in Molecular Recognition : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002A-2962-8 %R 10.1021/acs.jpcb.5b11593 %7 2016 %D 2016 %J The Journal of Physical Chemistry B %O J. Phys. Chem. B %V 120 %N 9 %& 2138 %P 2138 - 2144 %I American Chemical Society %C Washington, D.C. %@ false
2. Auffray C, Balling R, Barroso I, Bencze L, Blomberg N, Bock C, Conesa A, Del Signore S, Delogne C, Deyilee P, Di Meglio A, Eijkemans M, Flicek P, Graf N, Grimm V, Guchelaar H-J, Guo Y-K, Gut IG, Hanbury A, Hanif S, Hilgers R-D, Honrado Á, Hose DR, Houwing-Duistermaat J, Hubbard T, Janacek SH, Karanikas H, Kievits T, Kohler M, Kremer A, et al.: Making Sense of Big Data in Health Research: Towards an EU Action Plan. Genome Medicine 2016, 8.
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@article{Auffray2016, TITLE = {Making sense of big data in health research: {T}owards an {EU} action plan}, AUTHOR = {Auffray, Charles and Balling, Rudi and Barroso, In{\^e}s and Bencze, L{\'a}szl{\'o} and Blomberg, Niklas and Bock, Christoph and Conesa, Anna and Del Signore, Susanna and Delogne, Christophe and Deyilee, Peter and Di Meglio, Alberto and Eijkemans, Marinus and Flicek, Paul and Graf, Norbert and Grimm, Vera and Guchelaar, Henk-Jan and Guo, Yi-Ke and Gut, Ivo Glynne and Hanbury, Allan and Hanif, Shahid and Hilgers, Ralf-Dieter and Honrado, {\'A}ngel and Hose, D. Rod and Houwing-Duistermaat, Jeanine and Hubbard, Tim and Janacek, Sophie Helen and Karanikas, Haralampos and Kievits, Tim and Kohler, Manfred and Kremer, Andreas and Lanfear, Jerry and Lengauer, Thomas and Maes, Edith and Meert, Theo and M{\"u}ller, Werner and Nickel, D{\"o}rthe and Oledzki, Peter and Pedersen, Bertrand and Petkovic, Milan and Pliakos, Konstantinos and Rattray, Magnus and Red{\'o}n i M{\`a}s, Josep and Schneider, Reinhard and Sengstag, Thierry and Serra-Picamal, Xavier and Spek, Wouter and Vaas, Lea A. I. and van Batenburg, Okker and Vandelaer, Marc and Varnai, Peter and Villoslada, Pablo and Vizca{\'i}no, Juan Antonio and Wubbe, John Peter Mary and Zanetti, Gianluigi}, LANGUAGE = {eng}, DOI = {10.1186/s13073-016-0323-y}, PUBLISHER = {BioMedCentral}, ADDRESS = {London}, YEAR = {2016}, JOURNAL = {Genome Medicine}, VOLUME = {8}, EID = {71}, }
Endnote
%0 Journal Article %A Auffray, Charles %A Balling, Rudi %A Barroso, Inês %A Bencze, László %A Blomberg, Niklas %A Bock, Christoph %A Conesa, Anna %A Del Signore, Susanna %A Delogne, Christophe %A Deyilee, Peter %A Di Meglio, Alberto %A Eijkemans, Marinus %A Flicek, Paul %A Graf, Norbert %A Grimm, Vera %A Guchelaar, Henk-Jan %A Guo, Yi-Ke %A Gut, Ivo Glynne %A Hanbury, Allan %A Hanif, Shahid %A Hilgers, Ralf-Dieter %A Honrado, Ángel %A Hose, D. Rod %A Houwing-Duistermaat, Jeanine %A Hubbard, Tim %A Janacek, Sophie Helen %A Karanikas, Haralampos %A Kievits, Tim %A Kohler, Manfred %A Kremer, Andreas %A Lanfear, Jerry %A Lengauer, Thomas %A Maes, Edith %A Meert, Theo %A Müller, Werner %A Nickel, Dörthe %A Oledzki, Peter %A Pedersen, Bertrand %A Petkovic, Milan %A Pliakos, Konstantinos %A Rattray, Magnus %A Redón i Màs, Josep %A Schneider, Reinhard %A Sengstag, Thierry %A Serra-Picamal, Xavier %A Spek, Wouter %A Vaas, Lea A. I. %A van Batenburg, Okker %A Vandelaer, Marc %A Varnai, Peter %A Villoslada, Pablo %A Vizcaíno, Juan Antonio %A Wubbe, John Peter Mary %A Zanetti, Gianluigi %+ External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations %T Making Sense of Big Data in Health Research: Towards an EU Action Plan : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002A-F908-8 %R 10.1186/s13073-016-0323-y %2 PMC4919856 %7 2016 %D 2016 %J Genome Medicine %V 8 %Z sequence number: 71 %I BioMedCentral %C London
3. Berger B, Gaasterland T, Lengauer T, Orengo C, Gaeta B, Markel S, Valencia A: ISCB’s Initial Reaction to The New England Journal of Medicine Editorial on Data Sharing. PLoS Computational Biology 2016, 12.
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@article{Berger2016, TITLE = {{ISCB}{\textquoteright}s Initial Reaction to The New England Journal of Medicine Editorial on Data Sharing}, AUTHOR = {Berger, Bonnie and Gaasterland, Terry and Lengauer, Thomas and Orengo, Christine and Gaeta, Bruno and Markel, Scott and Valencia, Alfonso}, LANGUAGE = {eng}, ISSN = {1553-734X}, DOI = {10.1371/journal.pcbi.1004816}, PUBLISHER = {Public Library of Science}, ADDRESS = {San Francisco, CA}, YEAR = {2016}, JOURNAL = {PLoS Computational Biology}, VOLUME = {12}, NUMBER = {3}, EID = {e1004816}, }
Endnote
%0 Journal Article %A Berger, Bonnie %A Gaasterland, Terry %A Lengauer, Thomas %A Orengo, Christine %A Gaeta, Bruno %A Markel, Scott %A Valencia, Alfonso %+ External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations %T ISCB’s Initial Reaction to The New England Journal of Medicine Editorial on Data Sharing : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002A-FD6F-D %R 10.1371/journal.pcbi.1004816 %7 2016 %D 2016 %J PLoS Computational Biology %V 12 %N 3 %Z sequence number: e1004816 %I Public Library of Science %C San Francisco, CA %@ false
4. Carlson JM, Du VY, Pfeifer N, Bansal A, Tan VYF, Power K, Brumme CJ, Kreimer A, DeZiel CE, Fusi N, Schaefer M, Brockman MA, Gilmour J, Price MA, Kilembe W, Haubrich R, John M, Mallal S, Shapiro R, Frater J, Harrigan PR, Ndung’u T, Allen S, Heckerman D, Sidney J, Allen TM, Goulder PJR, Brumme ZL, Hunter E, Goepfert PA: Impact of Pre-adapted HIV Transmission. Nature Medicine 2016, 22.
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@article{Carlson2016, TITLE = {Impact of Pre-adapted {HIV} Transmission}, AUTHOR = {Carlson, Jonathan M. and Du, Victor Y. and Pfeifer, Nico and Bansal, Anju and Tan, Vincent Y. F. and Power, Karen and Brumme, Chanson J. and Kreimer, Anat and DeZiel, Charles E. and Fusi, Nicolo and Schaefer, Malinda and Brockman, Mark A. and Gilmour, Jil and Price, Matt A. and Kilembe, William and Haubrich, Richard and John, Mina and Mallal, Simon and Shapiro, Roger and Frater, John and Harrigan, P. Richard and Ndung'u, Thumbi and Allen, Susan and Heckerman, David and Sidney, John and Allen, Todd M. and Goulder, Philip J. R. and Brumme, Zabrina L. and Hunter, Eric and Goepfert, Paul A.}, LANGUAGE = {eng}, ISSN = {1078-8956}, DOI = {10.1038/nm.4100}, PUBLISHER = {Nature Pub. Co.}, ADDRESS = {New York, NY}, YEAR = {2016}, DATE = {2016}, JOURNAL = {Nature Medicine}, VOLUME = {22}, PAGES = {606--613}, }
Endnote
%0 Journal Article %A Carlson, Jonathan M. %A Du, Victor Y. %A Pfeifer, Nico %A Bansal, Anju %A Tan, Vincent Y. F. %A Power, Karen %A Brumme, Chanson J. %A Kreimer, Anat %A DeZiel, Charles E. %A Fusi, Nicolo %A Schaefer, Malinda %A Brockman, Mark A. %A Gilmour, Jil %A Price, Matt A. %A Kilembe, William %A Haubrich, Richard %A John, Mina %A Mallal, Simon %A Shapiro, Roger %A Frater, John %A Harrigan, P. Richard %A Ndung'u, Thumbi %A Allen, Susan %A Heckerman, David %A Sidney, John %A Allen, Todd M. %A Goulder, Philip J. R. %A Brumme, Zabrina L. %A Hunter, Eric %A Goepfert, Paul A. %+ External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations %T Impact of Pre-adapted HIV Transmission : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002A-ED12-F %R 10.1038/nm.4100 %7 2016 %D 2016 %J Nature Medicine %O Nat. Med. %V 22 %& 606 %P 606 - 613 %I Nature Pub. Co. %C New York, NY %@ false
5. Doncheva NT: Network Biology Methods for Functional Characterization and Integrative Prioritization of Disease Genes and Proteins. Universität des Saarlandes; 2016.
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@phdthesis{DonchevaPhD2016, TITLE = {Network Biology Methods for Functional Characterization and Integrative Prioritization of Disease Genes and Proteins}, AUTHOR = {Doncheva, Nadezhda Tsankova}, LANGUAGE = {eng}, URL = {urn:nbn:de:bsz:291-scidok-65957}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2016}, DATE = {2016}, }
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%0 Thesis %A Doncheva, Nadezhda Tsankova %Y Albrecht, Mario %A referee: Lengauer, Thomas %A referee: Lenhof, Hans-Peter %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society International Max Planck Research School, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T Network Biology Methods for Functional Characterization and Integrative Prioritization of Disease Genes and Proteins : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002B-1921-A %U urn:nbn:de:bsz:291-scidok-65957 %I Universität des Saarlandes %C Saarbrücken %D 2016 %P XII, 242 p. %V phd %9 phd %U http://scidok.sulb.uni-saarland.de/volltexte/2016/6595/http://scidok.sulb.uni-saarland.de/doku/lic_ohne_pod.php?la=de
6. Durai DA, Schulz MH: Informed kmer Selection for de novo Transcriptome Assembly. Bioinformatics 2016, 32.
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@article{Durai2016, TITLE = {Informed $k$mer Selection for $de$ $novo$ Transcriptome Assembly}, AUTHOR = {Durai, Dilip A. and Schulz, Marcel H.}, LANGUAGE = {eng}, ISSN = {1367-4803}, DOI = {10.1093/bioinformatics/btw217}, PUBLISHER = {Oxford University Press}, ADDRESS = {Oxford}, YEAR = {2016}, DATE = {2016}, JOURNAL = {Bioinformatics}, VOLUME = {32}, NUMBER = {11}, PAGES = {1670--1677}, }
Endnote
%0 Journal Article %A Durai, Dilip A. %A Schulz, Marcel H. %+ External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Informed kmer Selection for de novo Transcriptome Assembly : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002A-F53A-5 %R 10.1093/bioinformatics/btw217 %2 PMC4892416 %7 2016 %D 2016 %J Bioinformatics %V 32 %N 11 %& 1670 %P 1670 - 1677 %I Oxford University Press %C Oxford %@ false
7. Garg S, Martin M, Marschall T: Read-based Phasing of Related Individuals. Bioinformatics (Proc ISMB 2016) 2016, 32.
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@article{GargMarschall2016, TITLE = {Read-based Phasing of Related Individuals}, AUTHOR = {Garg, Shilpa and Martin, Marcel and Marschall, Tobias}, LANGUAGE = {eng}, ISSN = {1367-4803}, DOI = {10.1093/bioinformatics/btw276}, PUBLISHER = {Oxford University Press}, ADDRESS = {Oxford}, YEAR = {2016}, DATE = {2016}, JOURNAL = {Bioinformatics (Proc. ISMB)}, VOLUME = {32}, NUMBER = {12}, PAGES = {i234--i242}, BOOKTITLE = {ISMB 2016 Proceedings}, EDITOR = {Baldi, Pierre and Przytycka, Teresa}, }
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%0 Journal Article %A Garg, Shilpa %A Martin, Marcel %A Marschall, Tobias %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Read-based Phasing of Related Individuals : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002A-F931-A %R 10.1093/bioinformatics/btw276 %2 PMC4908360 %7 2016 %D 2016 %J Bioinformatics %V 32 %N 12 %& i234 %P i234 - i242 %I Oxford University Press %C Oxford %@ false %B ISMB 2016 Proceedings %O July 8 to July 12, 2016, Orlando, Florida 24th Annual Conference Intelligent Systems for Molecular Biology ISMB 2016
8. Götz U, Marker S, Cheaib M, Andresen K, Shrestha S, Durai DA, Nordström K, Schulz MH, Simon M: Two Sets of RNAi Components are Required for Heterochromatin Formation in Trans Triggered by Truncated Transgenes. Nucleic Acids Research (London) 2016, 44.
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@article{Goetz2016, TITLE = {Two Sets of {RNA}i Components are Required for Heterochromatin Formation in Trans Triggered by Truncated Transgenes}, AUTHOR = {G{\"o}tz, Ulrike and Marker, Simone and Cheaib, Miriam and Andresen, Karsten and Shrestha, Simon and Durai, Dilip Ariyur and Nordstr{\"o}m, Karl and Schulz, Marcel H. and Simon, Martin}, LANGUAGE = {eng}, ISSN = {0305-1048}, DOI = {10.1093/nar/gkw267}, PUBLISHER = {Oxford University Press}, ADDRESS = {Oxford}, YEAR = {2016}, DATE = {2016}, JOURNAL = {Nucleic Acids Research (London)}, VOLUME = {44}, NUMBER = {12}, PAGES = {5908--5923}, }
Endnote
%0 Journal Article %A Götz, Ulrike %A Marker, Simone %A Cheaib, Miriam %A Andresen, Karsten %A Shrestha, Simon %A Durai, Dilip Ariyur %A Nordström, Karl %A Schulz, Marcel H. %A Simon, Martin %+ External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T Two Sets of RNAi Components are Required for Heterochromatin Formation in Trans Triggered by Truncated Transgenes : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002B-16B8-E %R 10.1093/nar/gkw267 %7 2016 %D 2016 %J Nucleic Acids Research (London) %O Nucleic Acids Res %V 44 %N 12 %& 5908 %P 5908 - 5923 %I Oxford University Press %C Oxford %@ false
9. Hauschild A-C: Computational Methods for Breath Metabolomics in Clinical Diagnostics. Universität des Saarlandes; 2016.
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@phdthesis{Hauschild_PhD2016, TITLE = {Computational Methods for Breath Metabolomics in Clinical Diagnostics}, AUTHOR = {Hauschild, Anne-Christin}, LANGUAGE = {eng}, URL = {urn:nbn:de:bsz:291-scidok-65874}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2016}, DATE = {2016}, }
Endnote
%0 Thesis %A Hauschild, Anne-Christin %Y Helms, Volkhard %A referee: Baumbach, Jan %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society International Max Planck Research School, MPI for Informatics, Max Planck Society External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Computational Methods for Breath Metabolomics in Clinical Diagnostics : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002B-0C18-7 %U urn:nbn:de:bsz:291-scidok-65874 %I Universität des Saarlandes %C Saarbrücken %D 2016 %P 188 p. %V phd %9 phd %U http://scidok.sulb.uni-saarland.de/doku/lic_ohne_pod.php?la=dehttp://scidok.sulb.uni-saarland.de/volltexte/2016/6587/
10. Kalaghatgi P, Sikorski AM, Knops E, Rupp D, Sierra S, Heger E, Neumann-Fraune M, Beggel B, Walker A, Timm J, Walter H, Obermeier M, Kaiser R, Bartenschlager R, Lengauer T: Geno2pheno [HCV] -- A Web-based Interpretation System to Support Hepatitis C Treatment Decisions in the Era of Direct-Acting Antiviral Agents. PLoS One 2016, 11.
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@article{KalaghatgiPLOSone2016, TITLE = {{Geno2pheno} [{HCV}] -- A Web-based Interpretation System to Support Hepatitis {C} Treatment Decisions in the Era of Direct-Acting Antiviral Agents}, AUTHOR = {Kalaghatgi, Prabhav and Sikorski, Anna Maria and Knops, Elena and Rupp, Daniel and Sierra, Saleta and Heger, Eva and Neumann-Fraune, Maria and Beggel, Bastian and Walker, Andreas and Timm, J{\"o}rg and Walter, Hauke and Obermeier, Martin and Kaiser, Rolf and Bartenschlager, Ralf and Lengauer, Thomas}, LANGUAGE = {eng}, ISSN = {1932-6203}, DOI = {10.1371/journal.pone.0155869}, PUBLISHER = {Public Library of Science}, ADDRESS = {San Francisco, CA}, YEAR = {2016}, JOURNAL = {PLoS One}, VOLUME = {11}, NUMBER = {5}, EID = {e0155869}, }
Endnote
%0 Journal Article %A Kalaghatgi, Prabhav %A Sikorski, Anna Maria %A Knops, Elena %A Rupp, Daniel %A Sierra, Saleta %A Heger, Eva %A Neumann-Fraune, Maria %A Beggel, Bastian %A Walker, Andreas %A Timm, Jörg %A Walter, Hauke %A Obermeier, Martin %A Kaiser, Rolf %A Bartenschlager, Ralf %A Lengauer, Thomas %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Geno2pheno [HCV] -- A Web-based Interpretation System to Support Hepatitis C Treatment Decisions in the Era of Direct-Acting Antiviral Agents : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002A-EB8A-2 %R 10.1371/journal.pone.0155869 %2 PMC4873220 %7 2016-05-19 %D 2016 %8 19.05.2016 %J PLoS One %V 11 %N 5 %Z sequence number: e0155869 %I Public Library of Science %C San Francisco, CA %@ false
11. Kartashev V, Döring M, Nieto L, Coletta E, Kaiser R, Sierra S: New Findings in HCV Genotype Distribution in Selected West European, Russian and Israeli Regions. Journal of Clinical Virology 2016, 81.
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@article{Kartashev2016, TITLE = {New findings in {HCV} genotype distribution in selected {West European}, {Russian} and {Israeli} regions}, AUTHOR = {Kartashev, Vladimir and D{\"o}ring, Matthias and Nieto, Leonardo and Coletta, Eleda and Kaiser, Rolf and Sierra, Saleta}, LANGUAGE = {eng}, ISSN = {1386-6532}, DOI = {10.1016/j.jcv.2016.05.010}, PUBLISHER = {Elsevier}, ADDRESS = {Amsterdam}, YEAR = {2016}, DATE = {2016}, JOURNAL = {Journal of Clinical Virology}, VOLUME = {81}, PAGES = {82--89}, }
Endnote
%0 Journal Article %A Kartashev, Vladimir %A Döring, Matthias %A Nieto, Leonardo %A Coletta, Eleda %A Kaiser, Rolf %A Sierra, Saleta %+ External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations %T New Findings in HCV Genotype Distribution in Selected West European, Russian and Israeli Regions : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002A-F8EB-0 %R 10.1016/j.jcv.2016.05.010 %7 2016-05-24 %D 2016 %J Journal of Clinical Virology %V 81 %& 82 %P 82 - 89 %I Elsevier %C Amsterdam %@ false
12. Lawyer G: Measuring the Potential of Individual Airports for Pandemic Spread over the World Airline Network. BMC Infectious Diseases 2016, 16.
Abstract
ABSTRACT: BACKGROUND: Massive growth in human mobility has dramatically increased the risk and rate of pandemic spread. Macro-level descriptors of the topology of the World Airline Network (WAN) explains middle and late stage dynamics of pandemic spread mediated by this network, but necessarily regard early stage variation as stochastic. We propose that much of this early stage variation can be explained by appropriately characterizing the local network topology surrounding an outbreak’s debut location. METHODS: Based on a model of the WAN derived from public data, we measure for each airport the expected force of infection (AEF) which a pandemic originating at that airport would generate, assuming an epidemic process which transmits from airport to airport via scheduled commercial flights. We observe, for a subset of world airports, the minimum transmission rate at which a disease becomes pandemically competent at each airport. We also observe, for a larger subset, the time until a pandemically competent outbreak achieves pandemic status given its debut location. Observations are generated using a highly sophisticated metapopulation reaction-diffusion simulator under a disease model known to well replicate the 2009 influenza pandemic. The robustness of the AEF measure to model misspecification is examined by degrading the underlying model WAN. RESULTS: AEF powerfully explains pandemic risk, showing correlation of 0.90 to the transmission level needed to give a disease pandemic competence, and correlation of 0.85 to the delay until an outbreak becomes a pandemic. The AEF is robust to model misspecification. For 97 % of airports, removing 15 % of airports from the model changes their AEF metric by less than 1 %. CONCLUSIONS: Appropriately summarizing the size, shape, and diversity of an airport’s local neighborhood in the WAN accurately explains much of the macro-level stochasticity in pandemic outcomes.
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@article{Lawyer2016BMC, TITLE = {Measuring the Potential of Individual Airports for Pandemic Spread over the World Airline Network}, AUTHOR = {Lawyer, Glenn}, LANGUAGE = {eng}, ISSN = {1471-2334}, DOI = {10.1186/s12879-016-1350-4}, PUBLISHER = {BioMed Central Ltd.}, ADDRESS = {London, UK}, YEAR = {2016}, ABSTRACT = {ABSTRACT: BACKGROUND: Massive growth in human mobility has dramatically increased the risk and rate of pandemic spread. Macro-level descriptors of the topology of the World Airline Network (WAN) explains middle and late stage dynamics of pandemic spread mediated by this network, but necessarily regard early stage variation as stochastic. We propose that much of this early stage variation can be explained by appropriately characterizing the local network topology surrounding an outbreak{\textquoteright}s debut location. METHODS: Based on a model of the WAN derived from public data, we measure for each airport the expected force of infection (AEF) which a pandemic originating at that airport would generate, assuming an epidemic process which transmits from airport to airport via scheduled commercial flights. We observe, for a subset of world airports, the minimum transmission rate at which a disease becomes pandemically competent at each airport. We also observe, for a larger subset, the time until a pandemically competent outbreak achieves pandemic status given its debut location. Observations are generated using a highly sophisticated metapopulation reaction-diffusion simulator under a disease model known to well replicate the 2009 influenza pandemic. The robustness of the AEF measure to model misspecification is examined by degrading the underlying model WAN. RESULTS: AEF powerfully explains pandemic risk, showing correlation of 0.90 to the transmission level needed to give a disease pandemic competence, and correlation of 0.85 to the delay until an outbreak becomes a pandemic. The AEF is robust to model misspecification. For 97 % of airports, removing 15 % of airports from the model changes their AEF metric by less than 1 %. CONCLUSIONS: Appropriately summarizing the size, shape, and diversity of an airport{\textquoteright}s local neighborhood in the WAN accurately explains much of the macro-level stochasticity in pandemic outcomes.}, JOURNAL = {BMC Infectious Diseases}, VOLUME = {16}, NUMBER = {1}, EID = {70}, }
Endnote
%0 Journal Article %A Lawyer, Glenn %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Measuring the Potential of Individual Airports for Pandemic Spread over the World Airline Network : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0029-C693-A %R 10.1186/s12879-016-1350-4 %7 2016-02-09 %D 2016 %8 09.02.2016 %X ABSTRACT: BACKGROUND: Massive growth in human mobility has dramatically increased the risk and rate of pandemic spread. Macro-level descriptors of the topology of the World Airline Network (WAN) explains middle and late stage dynamics of pandemic spread mediated by this network, but necessarily regard early stage variation as stochastic. We propose that much of this early stage variation can be explained by appropriately characterizing the local network topology surrounding an outbreak’s debut location. METHODS: Based on a model of the WAN derived from public data, we measure for each airport the expected force of infection (AEF) which a pandemic originating at that airport would generate, assuming an epidemic process which transmits from airport to airport via scheduled commercial flights. We observe, for a subset of world airports, the minimum transmission rate at which a disease becomes pandemically competent at each airport. We also observe, for a larger subset, the time until a pandemically competent outbreak achieves pandemic status given its debut location. Observations are generated using a highly sophisticated metapopulation reaction-diffusion simulator under a disease model known to well replicate the 2009 influenza pandemic. The robustness of the AEF measure to model misspecification is examined by degrading the underlying model WAN. RESULTS: AEF powerfully explains pandemic risk, showing correlation of 0.90 to the transmission level needed to give a disease pandemic competence, and correlation of 0.85 to the delay until an outbreak becomes a pandemic. The AEF is robust to model misspecification. For 97 % of airports, removing 15 % of airports from the model changes their AEF metric by less than 1 %. CONCLUSIONS: Appropriately summarizing the size, shape, and diversity of an airport’s local neighborhood in the WAN accurately explains much of the macro-level stochasticity in pandemic outcomes. %J BMC Infectious Diseases %V 16 %N 1 %Z sequence number: 70 %I BioMed Central Ltd. %C London, UK %@ false
13. Li J, Klughammer J, Farlik M, Penz T, Spittler A, Barbieux C, Berishvili E, Bock C, Kubicek S: Single-cell Transcriptomes Reveal Characteristic Features of Human Pancreatic Islet Cell Types. EMBO Reports 2016, 17.
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@article{Li2015EMBO, TITLE = {Single-cell Transcriptomes Reveal Characteristic Features of Human Pancreatic Islet Cell Types}, AUTHOR = {Li, Jin and Klughammer, Johanna and Farlik, Matthias and Penz, Thomas and Spittler, Andreas and Barbieux, Charlotte and Berishvili, Ekaterine and Bock, Christoph and Kubicek, Stefan}, LANGUAGE = {eng}, ISSN = {1469-221X}, DOI = {10.15252/embr.201540946}, PUBLISHER = {Published for EMBO by Oxford University Press}, ADDRESS = {Oxford, UK}, YEAR = {2016}, DATE = {2016}, JOURNAL = {EMBO Reports}, VOLUME = {17}, NUMBER = {2}, PAGES = {178--187}, }
Endnote
%0 Journal Article %A Li, Jin %A Klughammer, Johanna %A Farlik, Matthias %A Penz, Thomas %A Spittler, Andreas %A Barbieux, Charlotte %A Berishvili, Ekaterine %A Bock, Christoph %A Kubicek, Stefan %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T Single-cell Transcriptomes Reveal Characteristic Features of Human Pancreatic Islet Cell Types : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0029-4243-A %R 10.15252/embr.201540946 %7 2015-12-21 %D 2016 %J EMBO Reports %O EMBO Rep. %V 17 %N 2 %& 178 %P 178 - 187 %I Published for EMBO by Oxford University Press %C Oxford, UK %@ false %U http://onlinelibrary.wiley.com/doi/10.15252/embr.201540946/pdf
14. Malek M, Ibragimov R, Albrecht M, Baumbach J: CytoGEDEVO-global Alignment of Biological Networks with Cytoscape. Bioinformatics 2016, 32.
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@article{Malek2016, TITLE = {{CytoGEDEVO}-global alignment of biological networks with {Cytoscape}}, AUTHOR = {Malek, Maximilian and Ibragimov, Rashid and Albrecht, Mario and Baumbach, Jan}, LANGUAGE = {eng}, ISSN = {1367-4803}, DOI = {10.1093/bioinformatics/btv732}, PUBLISHER = {Oxford University Press}, ADDRESS = {Oxford}, YEAR = {2016}, DATE = {2016}, JOURNAL = {Bioinformatics}, VOLUME = {32}, NUMBER = {8}, PAGES = {1259--1261}, }
Endnote
%0 Journal Article %A Malek, Maximilian %A Ibragimov, Rashid %A Albrecht, Mario %A Baumbach, Jan %+ External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T CytoGEDEVO-global Alignment of Biological Networks with Cytoscape : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002A-C477-9 %R 10.1093/bioinformatics/btv732 %7 2015-12-14 %D 2016 %J Bioinformatics %V 32 %N 8 %& 1259 %P 1259 - 1261 %I Oxford University Press %C Oxford %@ false
15. Mueller SC, Backes C, Gress A, Baumgarten N, Kalinina OV, Moll A, Kohlbacher O, Meese E, Keller A: BALL-SNPgp -- From Genetic Variants Toward Computational Diagnostics. Bioinformatics 2016, 32.
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@article{MuellerBioinformatics2016, TITLE = {{BALL}-{SNPgp} -- From Genetic Variants Toward Computational Diagnostics}, AUTHOR = {Mueller, Sabine C. and Backes, Christina and Gress, Alexander and Baumgarten, Nina and Kalinina, Olga V. and Moll, Andreas and Kohlbacher, Oliver and Meese, Eckart and Keller, Andreas}, LANGUAGE = {eng}, ISSN = {1367-4803}, DOI = {10.1093/bioinformatics/btw084}, PUBLISHER = {Oxford University Press}, ADDRESS = {Oxford}, YEAR = {2016}, DATE = {2016}, JOURNAL = {Bioinformatics}, VOLUME = {32}, NUMBER = {12}, PAGES = {1888--1890}, }
Endnote
%0 Journal Article %A Mueller, Sabine C. %A Backes, Christina %A Gress, Alexander %A Baumgarten, Nina %A Kalinina, Olga V. %A Moll, Andreas %A Kohlbacher, Oliver %A Meese, Eckart %A Keller, Andreas %+ External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations %T BALL-SNPgp -- From Genetic Variants Toward Computational Diagnostics : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002B-1954-5 %R 10.1093/bioinformatics/btw084 %7 2016 %D 2016 %J Bioinformatics %V 32 %N 12 %& 1888 %P 1888 - 1890 %I Oxford University Press %C Oxford %@ false
16. Peiffer K-H, Sommer L, Susser S, Vermehren J, Herrmann E, Döring M, Dietz J, Perner D, Berkowski C, Zeuzem S, Sarrazin C: Interferon Lambda 4 Genotypes and Resistance-associated Variants in Patients Infected with Hepatitis C Virus Genotypes 1 and 3. Heptatology 2016, 63.
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@article{Pfeiffer2015, TITLE = {Interferon Lambda 4 Genotypes and Resistance-associated Variants in Patients Infected with Hepatitis C Virus Genotypes 1 and 3}, AUTHOR = {Peiffer, Kai-Henrik and Sommer, Lisa and Susser, Simone and Vermehren, Johannes and Herrmann, Eva and D{\"o}ring, Matthias and Dietz, Julia and Perner, Dany and Berkowski, Caterina and Zeuzem, Stefan and Sarrazin, Christoph}, LANGUAGE = {eng}, ISSN = {1527-3350}, DOI = {10.1002/hep.28255}, PUBLISHER = {Wiley}, ADDRESS = {New York, NY}, YEAR = {2016}, DATE = {2016}, JOURNAL = {Heptatology}, VOLUME = {63}, NUMBER = {1}, PAGES = {63--73}, }
Endnote
%0 Journal Article %A Peiffer, Kai-Henrik %A Sommer, Lisa %A Susser, Simone %A Vermehren, Johannes %A Herrmann, Eva %A Döring, Matthias %A Dietz, Julia %A Perner, Dany %A Berkowski, Caterina %A Zeuzem, Stefan %A Sarrazin, Christoph %+ External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations %T Interferon Lambda 4 Genotypes and Resistance-associated Variants in Patients Infected with Hepatitis C Virus Genotypes 1 and 3 : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0029-1864-F %R 10.1002/hep.28255 %7 2015-11-25 %D 2016 %J Heptatology %V 63 %N 1 %& 63 %P 63 - 73 %I Wiley %C New York, NY %@ false
17. Rendeiro AF, Schmidl C, Strefford JC, Walewska R, Davis Z, Farlik M, Oscier D, Bock C: Chromatin Accessibility Maps of Chronic Lymphocytic Leukaemia Identify Subtype-specific Epigenome Signatures and Transcription Regulatory networks. Nature Communications 2016, 7.
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@article{Rendeiro2016, TITLE = {Chromatin Accessibility Maps of Chronic Lymphocytic Leukaemia Identify Subtype-specific Epigenome Signatures and Transcription Regulatory networks}, AUTHOR = {Rendeiro, Andr{\'e} F. and Schmidl, Christian and Strefford, Jonathan C. and Walewska, Renata and Davis, Zadie and Farlik, Matthias and Oscier, David and Bock, Christoph}, LANGUAGE = {eng}, ISSN = {2041-1723}, DOI = {10.1038/ncomms11938}, PUBLISHER = {Nature Publishing Group}, ADDRESS = {London}, YEAR = {2016}, JOURNAL = {Nature Communications}, VOLUME = {7}, EID = {11938}, }
Endnote
%0 Journal Article %A Rendeiro, André F. %A Schmidl, Christian %A Strefford, Jonathan C. %A Walewska, Renata %A Davis, Zadie %A Farlik, Matthias %A Oscier, David %A Bock, Christoph %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Chromatin Accessibility Maps of Chronic Lymphocytic Leukaemia Identify Subtype-specific Epigenome Signatures and Transcription Regulatory networks : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002B-133F-B %R 10.1038/ncomms11938 %7 2016 %D 2016 %J Nature Communications %O Nat. Commun. %V 7 %Z sequence number: 11938 %I Nature Publishing Group %C London %@ false
18. Schoofs T, Klein F, Braunschweig M, Kreider EF, Feldmann A, Nogueira L, Oliveira T, Lorenzi JCC, Parrish EH, Learn GH, West AP, Bjorkman PJ, Schlesinger S, Seaman MS, Czartoski J, McElrath MJ, Pfeifer N, Hahn BH, Caskey M, Nussenzweig MC: HIV-1 Therapy with Monoclonal Antibody 3BNC117 Elicits Host Immune Responses Against HIV-1. Science 2016, 352.
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@article{Schoofs2016, TITLE = {{HIV}-1 Therapy with Monoclonal Antibody 3BNC117 Elicits Host Immune Responses Against {HIV}-1}, AUTHOR = {Schoofs, Till and Klein, Florian and Braunschweig, Malte and Kreider, Edward F. and Feldmann, Anna and Nogueira, Lilian and Oliveira, Thiago and Lorenzi, Julio C. C. and Parrish, Erica H. and Learn, Gerald H. and West, Anthony P. and Bjorkman, Pamela J. and Schlesinger, Sarah and Seaman, Michael S. and Czartoski, Julie and McElrath, M. Juliana and Pfeifer, Nico and Hahn, Beatrice H. and Caskey, Marina and Nussenzweig, Michel C.}, LANGUAGE = {eng}, ISSN = {0036-8075}, DOI = {10.1126/science.aaf0972}, PUBLISHER = {AAAS}, ADDRESS = {Washington, DC}, YEAR = {2016}, DATE = {2016}, JOURNAL = {Science}, VOLUME = {352}, NUMBER = {6288}, PAGES = {997--1001}, }
Endnote
%0 Journal Article %A Schoofs, Till %A Klein, Florian %A Braunschweig, Malte %A Kreider, Edward F. %A Feldmann, Anna %A Nogueira, Lilian %A Oliveira, Thiago %A Lorenzi, Julio C. C. %A Parrish, Erica H. %A Learn, Gerald H. %A West, Anthony P. %A Bjorkman, Pamela J. %A Schlesinger, Sarah %A Seaman, Michael S. %A Czartoski, Julie %A McElrath, M. Juliana %A Pfeifer, Nico %A Hahn, Beatrice H. %A Caskey, Marina %A Nussenzweig, Michel C. %+ External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations %T HIV-1 Therapy with Monoclonal Antibody 3BNC117 Elicits Host Immune Responses Against HIV-1 : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002A-D9BC-3 %R 10.1126/science.aaf0972 %7 2016 %D 2016 %J Science %V 352 %N 6288 %& 997 %P 997 - 1001 %I AAAS %C Washington, DC %@ false
19. Sdelci S, Lardeau C-H, Tallant C, Klepsch F, Klaiber B, Bennett J, Rathert P, Schuster M, Penz T, Fedorov O, Superti-Furga G, Bock C, Zuber J, Huber KVM, Knapp S, Müller S, Kubicek S: Mapping the Chemical Chromatin Reactivation Landscape Identifies BRD4-TAF1 Cross-talk. Nature Chemical Biology 2016, 12.
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@article{Sdelci2016, TITLE = {Mapping the Chemical Chromatin Reactivation Landscape Identifies {BRD4}-{TAF1} Cross-talk}, AUTHOR = {Sdelci, Sara and Lardeau, Charles-Hugues and Tallant, Cynthia and Klepsch, Freya and Klaiber, Bj{\"o}rn and Bennett, James and Rathert, Philipp and Schuster, Michael and Penz, Thomas and Fedorov, Oleg and Superti-Furga, Guilio and Bock, Christoph and Zuber, Johannes and Huber, Kilan V. M. and Knapp, Stefan and M{\"u}ller, Susanne and Kubicek, Stefan}, LANGUAGE = {eng}, ISSN = {1552-4450}, DOI = {10.1038/nchembio.2080}, PUBLISHER = {Nature Pub. Group}, ADDRESS = {New York, NY}, YEAR = {2016}, DATE = {2016}, JOURNAL = {Nature Chemical Biology}, VOLUME = {12}, PAGES = {504--510}, }
Endnote
%0 Journal Article %A Sdelci, Sara %A Lardeau, Charles-Hugues %A Tallant, Cynthia %A Klepsch, Freya %A Klaiber, Björn %A Bennett, James %A Rathert, Philipp %A Schuster, Michael %A Penz, Thomas %A Fedorov, Oleg %A Superti-Furga, Guilio %A Bock, Christoph %A Zuber, Johannes %A Huber, Kilan V. M. %A Knapp, Stefan %A Müller, Susanne %A Kubicek, Stefan %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations %T Mapping the Chemical Chromatin Reactivation Landscape Identifies BRD4-TAF1 Cross-talk : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002A-FC88-C %R 10.1038/nchembio.2080 %7 2016 %D 2016 %J Nature Chemical Biology %O Nat. Chem. Biol. %V 12 %& 504 %P 504 - 510 %I Nature Pub. Group %C New York, NY %@ false
20. Sheffield NC, Bock C: LOLA: Enrichment Analysis for Genomic Region Sets and Regulatory Elements in R and Bioconductor. Bioinformatics 2016, 32.
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@article{Sheffield2016, TITLE = {{LOLA}: enrichment analysis for genomic region sets and regulatory elements in {R} and {Bioconductor}}, AUTHOR = {Sheffield, Nathan C. and Bock, Christoph}, LANGUAGE = {eng}, ISSN = {1367-4803}, DOI = {10.1093/bioinformatics/btv612}, PUBLISHER = {Oxford University Press}, ADDRESS = {Oxford}, YEAR = {2016}, DATE = {2016}, JOURNAL = {Bioinformatics}, VOLUME = {32}, NUMBER = {4}, PAGES = {587--589}, }
Endnote
%0 Journal Article %A Sheffield, Nathan C. %A Bock, Christoph %+ External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T LOLA: Enrichment Analysis for Genomic Region Sets and Regulatory Elements in R and Bioconductor : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002A-0530-B %R 10.1093/bioinformatics/btv612 %7 2015-10-27 %D 2016 %J Bioinformatics %V 32 %N 4 %& 587 %P 587 - 589 %I Oxford University Press %C Oxford %@ false
21. St. John EP, Simen BB, Turenchalk GS, Brayerman MS, Abhate I, Aerssens J, Bouchez O, Gabriel C, Izopet J, Meixenberger K, Giallonardo F, Metzner KJ, Schlapbach R, Paredes R, Sakwa J, Schmitz-Agheguian GG, Victor M, Thielen A, Däumer MP, Lengauer T: A Follow-Up of the Multicenter Collaborative Study on HIV-1 Drug Resistance and Tropism Testing Using 454 Ultra Deep Pyrosequencing. PLoS One 2016, 11.
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@article{Lengauer2016PLoSOne, TITLE = {A Follow-Up of the Multicenter Collaborative Study on {HIV}-1 Drug Resistance and Tropism Testing Using 454 Ultra Deep Pyrosequencing}, AUTHOR = {St. John, Elizabeth P. and Simen, Birgitte B. and Turenchalk, Gregory S. and Brayerman, Michael S. and Abhate, Isabella and Aerssens, Jeroen and Bouchez, Olivier and Gabriel, Christian and Izopet, Jacques and Meixenberger, Karolin and Giallonardo, Francesca and Metzner, Karin J. and Schlapbach, Ralph and Paredes, Roger and Sakwa, James and Schmitz-Agheguian, Gudrun G. and Victor, Martin and Thielen, Alexander and D{\"a}umer, Martin P. and Lengauer, Thomas}, LANGUAGE = {eng}, ISSN = {1932-6203}, DOI = {10.1371/journal.pone.0146687}, PUBLISHER = {Public Library of Science}, ADDRESS = {San Francisco, CA}, YEAR = {2016}, JOURNAL = {PLoS One}, VOLUME = {11}, NUMBER = {1}, EID = {e0146687}, }
Endnote
%0 Journal Article %A St. John, Elizabeth P. %A Simen, Birgitte B. %A Turenchalk, Gregory S. %A Brayerman, Michael S. %A Abhate, Isabella %A Aerssens, Jeroen %A Bouchez, Olivier %A Gabriel, Christian %A Izopet, Jacques %A Meixenberger, Karolin %A Giallonardo, Francesca %A Metzner, Karin J. %A Schlapbach, Ralph %A Paredes, Roger %A Sakwa, James %A Schmitz-Agheguian, Gudrun G. %A Victor, Martin %A Thielen, Alexander %A Däumer, Martin P. %A Lengauer, Thomas %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T A Follow-Up of the Multicenter Collaborative Study on HIV-1 Drug Resistance and Tropism Testing Using 454 Ultra Deep Pyrosequencing : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002A-432C-1 %R 10.1371/journal.pone.0146687 %7 2016 %D 2016 %J PLoS One %V 11 %N 1 %Z sequence number: e0146687 %I Public Library of Science %C San Francisco, CA %@ false
22. Wallner S, Schröder C, Leitão E, Berulava T, Haak C, Beißer D, Rahmann S, Richter AS, Manke T, Bönisch U, Arrigoni L, Fröhler S, Klironomos F, Chen W, Rajewsky N, Müller F, Ebert P, Lengauer T, Barann M, Rosenstiel P, Gasparoni G, Nordström K, Walter J, Brors B, Zipprich G, Felder B, Klein-Hitpass L, Attenberger C, Schmitz G, Horsthemke B: Epigenetic Dynamics of Monocyte-to-Macrophage Differentiation. Epigenetics & Chromatin 2016, 9.
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@article{Wallner2016, TITLE = {Epigenetic Dynamics of Monocyte-to-Macrophage Differentiation}, AUTHOR = {Wallner, Stefan and Schr{\"o}der, Christopher and Leit{\~a}o, Elsa and Berulava, Tea and Haak, Claudia and Bei{\ss}er, Daniela and Rahmann, Sven and Richter, Andreas S. and Manke, Thomas and B{\"o}nisch, Ulrike and Arrigoni, Laura and Fr{\"o}hler, Sebastian and Klironomos, Filippos and Chen, Wei and Rajewsky, Nikolaus and M{\"u}ller, Fabian and Ebert, Peter and Lengauer, Thomas and Barann, Matthias and Rosenstiel, Philip and Gasparoni, Gilles and Nordstr{\"o}m, Karl and Walter, J{\"o}rn and Brors, Benedikt and Zipprich, Gideon and Felder, B{\"a}rbel and Klein-Hitpass, Ludger and Attenberger, Corinna and Schmitz, Gerd and Horsthemke, Bernhard}, LANGUAGE = {eng}, DOI = {10.1186/s13072-016-0079-z}, PUBLISHER = {BioMed Central}, ADDRESS = {London}, YEAR = {2016}, JOURNAL = {Epigenetics \& Chromatin}, VOLUME = {9}, EID = {33}, }
Endnote
%0 Journal Article %A Wallner, Stefan %A Schröder, Christopher %A Leitão, Elsa %A Berulava, Tea %A Haak, Claudia %A Beißer, Daniela %A Rahmann, Sven %A Richter, Andreas S. %A Manke, Thomas %A Bönisch, Ulrike %A Arrigoni, Laura %A Fröhler, Sebastian %A Klironomos, Filippos %A Chen, Wei %A Rajewsky, Nikolaus %A Müller, Fabian %A Ebert, Peter %A Lengauer, Thomas %A Barann, Matthias %A Rosenstiel, Philip %A Gasparoni, Gilles %A Nordström, Karl %A Walter, Jörn %A Brors, Benedikt %A Zipprich, Gideon %A Felder, Bärbel %A Klein-Hitpass, Ludger %A Attenberger, Corinna %A Schmitz, Gerd %A Horsthemke, Bernhard %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations %T Epigenetic Dynamics of Monocyte-to-Macrophage Differentiation : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002B-1691-6 %R 10.1186/s13072-016-0079-z %7 2016 %D 2016 %J Epigenetics & Chromatin %V 9 %Z sequence number: 33 %I BioMed Central %C London
23. Welsch C, Haselow K, Gouttenoire J, Schneider M, Morikawa K, Martinez Y, Susser S, Sarrazin C, Zeuzem S, Antes I, Moradpour D, Lange CM: Hepatitis C Virus Variants Resistant to Macrocyclic NS3-4A Inhibitors Subvert IFN-β Induction by Efficient MAVS Cleavage. Journal of Hepatology 2016, 62.
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@article{WelschJoH2016, TITLE = {Hepatitis {C} Virus Variants Resistant to Macrocyclic {NS3}-{4A} Inhibitors Subvert {IFN}-β Induction by Efficient {MAVS} Cleavage}, AUTHOR = {Welsch, Christoph and Haselow, Katrin and Gouttenoire, J{\'e}r{\^o}me and Schneider, Markus and Morikawa, Kenichi and Martinez, Yolanda and Susser, Simone and Sarrazin, Christoph and Zeuzem, Stefan and Antes, Iris and Moradpour, Darius and Lange, Christian M.}, LANGUAGE = {eng}, ISSN = {0168-8278}, DOI = {10.1016/j.jhep.2014.11.009}, PUBLISHER = {Elsevier}, ADDRESS = {Amsterdam}, YEAR = {2016}, DATE = {2016}, JOURNAL = {Journal of Hepatology}, VOLUME = {62}, NUMBER = {4}, PAGES = {779--784}, }
Endnote
%0 Journal Article %A Welsch, Christoph %A Haselow, Katrin %A Gouttenoire, Jérôme %A Schneider, Markus %A Morikawa, Kenichi %A Martinez, Yolanda %A Susser, Simone %A Sarrazin, Christoph %A Zeuzem, Stefan %A Antes, Iris %A Moradpour, Darius %A Lange, Christian M. %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations %T Hepatitis C Virus Variants Resistant to Macrocyclic NS3-4A Inhibitors Subvert IFN-β Induction by Efficient MAVS Cleavage : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002A-433B-0 %R 10.1016/j.jhep.2014.11.009 %7 2016 %D 2016 %J Journal of Hepatology %O J. Hepatol. %V 62 %N 4 %& 779 %P 779 - 784 %I Elsevier %C Amsterdam %@ false
2015
24. Abreu VAC, Almeida S, Tiwari S, Hassan SS, Mariano D, Silva A, Baumbach J, Azevedo V, Röttger R: CMRegNet -- An Interspecies Reference Database for Corynebacterial and Mycobacterial Regulatory Networks. BMC Genomics 2015, 16.
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@article{AbreuBMCGenomics2015, TITLE = {{CMRegNet} -- An Interspecies Reference Database for Corynebacterial and Mycobacterial Regulatory Networks}, AUTHOR = {Abreu, Vinicius A. C. and Almeida, Sintia and Tiwari, Sandeep and Hassan, Syed Shah and Mariano, Diego and Silva, Artur and Baumbach, Jan and Azevedo, Vasco and R{\"o}ttger, Richard}, LANGUAGE = {eng}, ISSN = {1471-2164}, URL = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4464113&tool=pmcentrez&rendertype=abstract}, DOI = {10.1186/s12864-015-1631-0}, PUBLISHER = {BioMed Central}, ADDRESS = {London}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, JOURNAL = {BMC Genomics}, VOLUME = {16}, NUMBER = {1}, EID = {452}, }
Endnote
%0 Journal Article %A Abreu, Vinicius A. C. %A Almeida, Sintia %A Tiwari, Sandeep %A Hassan, Syed Shah %A Mariano, Diego %A Silva, Artur %A Baumbach, Jan %A Azevedo, Vasco %A Röttger, Richard %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T CMRegNet -- An Interspecies Reference Database for Corynebacterial and Mycobacterial Regulatory Networks : %! {CMRegNet} -- An Interspecies Reference Database for Corynebacterial and Mycobacterial Regulatory Networks %G eng %U http://hdl.handle.net/11858/00-001M-0000-0027-ACBB-E %F OTHER: accessionPMC4464113 %F OTHER: pmcidPMC4464113 %F OTHER: pmc-uid4464113 %F OTHER: publisher-id1631 %R 10.1186/s12864-015-1631-0 %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4464113&tool=pmcentrez&rendertype=abstract %7 2015-06-11 %D 2015 %8 11.06.2015 %J BMC Genomics %V 16 %N 1 %Z sequence number: 452 %I BioMed Central %C London %@ false
25. Ahmad M, Helms V, Lengauer T, Kalinina OV: Enthalpy-entropy Compensation upon Molecular Conformational Changes. Journal of Chemical Theory and Computation 2015, 11.
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@article{Lengauer2015, TITLE = {Enthalpy-entropy Compensation upon Molecular Conformational Changes}, AUTHOR = {Ahmad, Mazen and Helms, Volkhard and Lengauer, Thomas and Kalinina, Olga V.}, LANGUAGE = {eng}, DOI = {10.1021/ct501161t}, PUBLISHER = {American Chemical Society}, ADDRESS = {Washington, D.C.}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, DATE = {2015}, JOURNAL = {Journal of Chemical Theory and Computation}, VOLUME = {11}, NUMBER = {4}, PAGES = {1410--1418}, }
Endnote
%0 Journal Article %A Ahmad, Mazen %A Helms, Volkhard %A Lengauer, Thomas %A Kalinina, Olga V. %+ External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Enthalpy-entropy Compensation upon Molecular Conformational Changes : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-E34E-B %R 10.1021/ct501161t %7 2015 %D 2015 %J Journal of Chemical Theory and Computation %O J. Chem. Theory Comput. %V 11 %N 4 %& 1410 %P 1410 - 1418 %I American Chemical Society %C Washington, D.C.
26. Ahmad M, Helms V, Lengauer T, Kalinina OV: How Molecular Conformational Changes Affect Changes in Free Energy. Journal of Chemical Theory and Computation 2015, 11.
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@article{AhmadJCTC2015, TITLE = {How Molecular Conformational Changes Affect Changes in Free Energy}, AUTHOR = {Ahmad, Mazen and Helms, Volkhard and Lengauer, Thomas and Kalinina, Olga V.}, LANGUAGE = {eng}, DOI = {10.1021/acs.jctc.5b00235}, PUBLISHER = {American Chemical Society}, ADDRESS = {Washington, D.C.}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, DATE = {2015}, JOURNAL = {Journal of Chemical Theory and Computation}, VOLUME = {11}, NUMBER = {7}, PAGES = {2945--2957}, }
Endnote
%0 Journal Article %A Ahmad, Mazen %A Helms, Volkhard %A Lengauer, Thomas %A Kalinina, Olga V. %+ External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T How Molecular Conformational Changes Affect Changes in Free Energy : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0028-4CAF-6 %R 10.1021/acs.jctc.5b00235 %7 2015 %D 2015 %J Journal of Chemical Theory and Computation %O J. Chem. Theory Comput. %V 11 %N 7 %& 2945 %P 2945 - 2957 %I American Chemical Society %C Washington, D.C.
27. Aldinucci M, Bracciali A, Marschall T, Patterson M, Pisanti N, Torquati M: High-Performance Haplotype Assembly. In Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB 2014). Springer; 2015. [Lecture Notes in Computer Science, vol. 8623]
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@inproceedings{MarschallLNBI15, TITLE = {High-Performance Haplotype Assembly}, AUTHOR = {Aldinucci, Marco and Bracciali, Andrea and Marschall, Tobias and Patterson, Murray and Pisanti, Nadia and Torquati, Massimo}, LANGUAGE = {eng}, ISBN = {978-3-319-24461-7}, DOI = {10.1007/978-3-319-24462-4_21}, PUBLISHER = {Springer}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2015}, BOOKTITLE = {Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB 2014)}, PAGES = {245--258}, SERIES = {Lecture Notes in Computer Science}, VOLUME = {8623}, ADDRESS = {Cambridge, UK}, }
Endnote
%0 Conference Proceedings %A Aldinucci, Marco %A Bracciali, Andrea %A Marschall, Tobias %A Patterson, Murray %A Pisanti, Nadia %A Torquati, Massimo %+ External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations %T High-Performance Haplotype Assembly : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0029-5D10-1 %R 10.1007/978-3-319-24462-4_21 %D 2015 %B 11th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics %Z date of event: 2014-06-26 - 2014-06-28 %C Cambridge, UK %B Computational Intelligence Methods for Bioinformatics and Biostatistics %P 245 - 258 %I Springer %@ 978-3-319-24461-7 %B Lecture Notes in Computer Science %N 8623
28. Amabile G, Di Ruscio A, Müller F, Welner RS, Yang H, Ebralidze AK, Zhong H, Levantini E, Qi L, Martinelli G, Brummelkamp T, Le Beau MM, Figueroa ME, Bock C, Tenen DG: Dissecting the Role of Aberrant DNA Methylation in Human Leukaemia. Nature Communications 2015, 6.
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@article{MullerBock2015, TITLE = {Dissecting the Role of Aberrant {DNA} Methylation in Human Leukaemia}, AUTHOR = {Amabile, Giovanni and Di Ruscio, Annalisa and M{\"u}ller, Fabian and Welner, Robert S. and Yang, Henry and Ebralidze, Alexander K. and Zhong, Hong and Levantini, Elena and Qi, Lihua and Martinelli, Giovanni and Brummelkamp, Thijn and Le Beau, Michelle M. and Figueroa, Maria E. and Bock, Christoph and Tenen, Daniel G.}, LANGUAGE = {eng}, ISSN = {2041-1723}, DOI = {10.1038/ncomms8091}, PUBLISHER = {Nature Publishing Group}, ADDRESS = {London}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, DATE = {2015}, JOURNAL = {Nature Communications}, VOLUME = {6}, EID = {7091}, }
Endnote
%0 Journal Article %A Amabile, Giovanni %A Di Ruscio, Annalisa %A Müller, Fabian %A Welner, Robert S. %A Yang, Henry %A Ebralidze, Alexander K. %A Zhong, Hong %A Levantini, Elena %A Qi, Lihua %A Martinelli, Giovanni %A Brummelkamp, Thijn %A Le Beau, Michelle M. %A Figueroa, Maria E. %A Bock, Christoph %A Tenen, Daniel G. %+ External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T Dissecting the Role of Aberrant DNA Methylation in Human Leukaemia : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0027-AD30-B %R 10.1038/ncomms8091 %7 2015 %D 2015 %J Nature Communications %O Nat. Commun. %V 6 %Z sequence number: 7091 %I Nature Publishing Group %C London %@ false
29. Andreassen OA, Desikan RS, Wang Y, Thompson WK, Schork AJ, Zuber V, Doncheva NT, Ellinghaus E, Albrecht M, Mattingsdal M, Franke A, Lie BA, Mills I, Aukrust P, McEvoy LK, Djurovic S, Karlsen TH, Dale AM: Abundant Genetic Overlap between Blood Lipids and Immune-Mediated Diseases Indicates Shared Molecular Genetic Mechanisms. PLoS ONE 2015, 10.
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@article{Andreassen2015, TITLE = {Abundant Genetic Overlap between Blood Lipids and Immune-Mediated Diseases Indicates Shared Molecular Genetic Mechanisms}, AUTHOR = {Andreassen, Ole A. and Desikan, Rahul S. and Wang, Yunpeng and Thompson, Wesley K. and Schork, Andrew J. and Zuber, Verena and Doncheva, Nadezhda Tsankova and Ellinghaus, Eva and Albrecht, Mario and Mattingsdal, Morten and Franke, Andre and Lie, Benedicte A. and Mills, Ian and Aukrust, P{\aa}l and McEvoy, Linda K. and Djurovic, Srdjan and Karlsen, Tom H. and Dale, Anders M.}, LANGUAGE = {eng}, ISSN = {1932-6203}, URL = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4390360&tool=pmcentrez&rendertype=abstract}, DOI = {10.1371/journal.pone.0123057}, PUBLISHER = {Public Library of Science}, ADDRESS = {San Francisco, CA}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, JOURNAL = {PLoS ONE}, VOLUME = {10}, NUMBER = {4}, EID = {e0123057}, }
Endnote
%0 Journal Article %A Andreassen, Ole A. %A Desikan, Rahul S. %A Wang, Yunpeng %A Thompson, Wesley K. %A Schork, Andrew J. %A Zuber, Verena %A Doncheva, Nadezhda Tsankova %A Ellinghaus, Eva %A Albrecht, Mario %A Mattingsdal, Morten %A Franke, Andre %A Lie, Benedicte A. %A Mills, Ian %A Aukrust, Pål %A McEvoy, Linda K. %A Djurovic, Srdjan %A Karlsen, Tom H. %A Dale, Anders M. %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations %T Abundant Genetic Overlap between Blood Lipids and Immune-Mediated Diseases Indicates Shared Molecular Genetic Mechanisms : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002A-3AB7-1 %2 PMC4390360 %F OTHER: pmc-uid4390360 %R 10.1371/journal.pone.0123057 %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4390360&tool=pmcentrez&rendertype=abstract %7 2015-04-08 %D 2015 %8 08.04.2015 %J PLoS ONE %V 10 %N 4 %Z sequence number: e0123057 %I Public Library of Science %C San Francisco, CA %@ false
30. Baumbach J, Guo J, Ibragimov R: Covering Tree with Stars. Journal of Combinatorial Optimization 2015, 29.
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@article{BaumbachJCombOptim2015, TITLE = {Covering Tree with Stars}, AUTHOR = {Baumbach, Jan and Guo, Jiong and Ibragimov, Rashid}, LANGUAGE = {eng}, ISSN = {1382-6905}, DOI = {10.1007/s10878-013-9692-y}, PUBLISHER = {Springer}, ADDRESS = {New York, NY}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, DATE = {2015}, JOURNAL = {Journal of Combinatorial Optimization}, VOLUME = {29}, NUMBER = {1}, PAGES = {141--152}, }
Endnote
%0 Journal Article %A Baumbach, Jan %A Guo, Jiong %A Ibragimov, Rashid %+ External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Covering Tree with Stars : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0026-BEEF-7 %R 10.1007/s10878-013-9692-y %7 2015 %D 2015 %J Journal of Combinatorial Optimization %V 29 %N 1 %& 141 %P 141 - 152 %I Springer %C New York, NY %@ false
31. Bellitto T, Marschall T, Schönhuth A, Klau GW: Next Generation Cluster Editing. 2015.
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@misc{MarschallPeer15, TITLE = {Next Generation Cluster Editing}, AUTHOR = {Bellitto, Thomas and Marschall, Tobias and Sch{\"o}nhuth, Alexander and Klau, Gunnar W.}, LANGUAGE = {eng}, DOI = {10.7287/peerj.preprints.1301v1}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, }
Endnote
%0 Report %A Bellitto, Thomas %A Marschall, Tobias %A Schönhuth, Alexander %A Klau, Gunnar W. %+ External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations %T Next Generation Cluster Editing : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0029-5E4D-6 %R 10.7287/peerj.preprints.1301v1 %D 2015 %8 13.08.2015 %Z Review method: peer-reviewed
32. Bock C, Bortolussi L, Krüger T, Mikeev L, Wolf V: Model-based Whole-genome Analysis of DNA Methylation Fidelity. In Hybrid Systems Biology (HSB 2015). Springer; 2015. [Lecture Notes in Bioinformatics, vol. 9271]
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@inproceedings{BockHSB2015, TITLE = {Model-Based Whole-Genome Analysis of {DNA} Methylation Fidelity}, AUTHOR = {Bock, Christoph and Bortolussi, Luca and Kr{\"u}ger, Thilo and Mikeev, Linar and Wolf, Verena}, LANGUAGE = {eng}, ISBN = {978-3-319-26915-3}, DOI = {10.1007/978-3-319-26916-0_8}, PUBLISHER = {Springer}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, DATE = {2015}, BOOKTITLE = {Hybrid Systems Biology (HSB 2015)}, EDITOR = {Abate, Alessandro and {\v S}afr{\'a}nek, David}, PAGES = {141--155}, SERIES = {Lecture Notes in Bioinformatics}, VOLUME = {9271}, ADDRESS = {Madrid, Spain}, }
Endnote
%0 Conference Proceedings %A Bock, Christoph %A Bortolussi, Luca %A Krüger, Thilo %A Mikeev, Linar %A Wolf, Verena %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations %T Model-based Whole-genome Analysis of DNA Methylation Fidelity : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002A-07ED-6 %R 10.1007/978-3-319-26916-0_8 %D 2015 %B 4th International Workshop on Hybrid Systems Biology %Z date of event: 2015-09-04 - 2015-09-05 %C Madrid, Spain %B Hybrid Systems Biology %E Abate, Alessandro; Šafránek , David %P 141 - 155 %I Springer %@ 978-3-319-26915-3 %B Lecture Notes in Bioinformatics %N 9271
33. Caprari S, Metzler S, Lengauer T, Kalinina OV: Sequence and Structure Analysis of Distantly-Related Viruses Reveals Extensive Gene Transfer between Viruses and Hosts and among Viruses. Viruses 2015, 7.
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@article{Caprari2015, TITLE = {Sequence and Structure Analysis of Distantly-Related Viruses Reveals Extensive Gene Transfer between Viruses and Hosts and among Viruses}, AUTHOR = {Caprari, Silvia and Metzler, Saskia and Lengauer, Thomas and Kalinina, Olga V.}, LANGUAGE = {eng}, ISSN = {1999-4915}, DOI = {10.3390/v7102882}, PUBLISHER = {MDPI}, ADDRESS = {Basel}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, JOURNAL = {Viruses}, VOLUME = {7}, NUMBER = {10}, PAGES = {5388--5409}, }
Endnote
%0 Journal Article %A Caprari, Silvia %A Metzler, Saskia %A Lengauer, Thomas %A Kalinina, Olga V. %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Sequence and Structure Analysis of Distantly-Related Viruses Reveals Extensive Gene Transfer between Viruses and Hosts and among Viruses : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0029-1A7E-5 %R 10.3390/v7102882 %2 PMC4632390 %7 2015 %D 2015 %J Viruses %V 7 %N 10 %& 5388 %P 5388 - 5409 %I MDPI %C Basel %@ false %U http://www.mdpi.com/1999-4915/7/10/2882
34. Charpentier C, Camacho R, Ruelle J, Eberle J, Gürtler L, Pironti A, Stürmer M, Brun-Vézinet F, Kaiser R, Descamps D, Obermeier M: HIV-2EU -- Supporting Standardized HIV-2 Drug-Resistance Interpretation in Europe: An Update. Clinical Infectious Diseases 2015, 61.
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@article{Charpentier2015, TITLE = {{HIV}-{2EU} -- {S}upporting Standardized {HIV}-2 Drug-Resistance Interpretation in Europe: {A}n Update}, AUTHOR = {Charpentier, Charlotte and Camacho, Ricardo and Ruelle, Jean and Eberle, Josef and G{\"u}rtler, Lutz and Pironti, Alejandro and St{\"u}rmer, Martin and Brun-V{\'e}zinet, Fran{\c c}oise and Kaiser, Rolf and Descamps, Diane and Obermeier, Martin}, LANGUAGE = {eng}, ISSN = {1058-4838}, DOI = {10.1093/cid/civ572}, PUBLISHER = {The University of Chicago Press}, ADDRESS = {Chicago, IL}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, DATE = {2015}, JOURNAL = {Clinical Infectious Diseases}, VOLUME = {61}, NUMBER = {8}, PAGES = {1347--1349}, }
Endnote
%0 Journal Article %A Charpentier, Charlotte %A Camacho, Ricardo %A Ruelle, Jean %A Eberle, Josef %A Gürtler, Lutz %A Pironti, Alejandro %A Stürmer, Martin %A Brun-Vézinet, Françoise %A Kaiser, Rolf %A Descamps, Diane %A Obermeier, Martin %+ External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations %T HIV-2EU -- Supporting Standardized HIV-2 Drug-Resistance Interpretation in Europe: An Update : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0028-F6CC-9 %R 10.1093/cid/civ572 %7 2015-07-17 %D 2015 %J Clinical Infectious Diseases %V 61 %N 8 %& 1347 %P 1347 - 1349 %I The University of Chicago Press %C Chicago, IL %@ false
35. Cheaib M, Dehghani Amirabad A, Nordström KJV, Schulz MH, Simon M: Epigenetic regulation of serotype expression antagonizes transcriptome dynamics in Paramecium tetraurelia. DNA Research: An International Journal for Rapid Publication of Reports on Genes and Genomes 2015, 22.
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@article{Cheaib2015, TITLE = {Epigenetic regulation of serotype expression antagonizes transcriptome dynamics in Paramecium tetraurelia}, AUTHOR = {Cheaib, Miriam and Dehghani Amirabad, Azim and Nordstr{\"o}m, Karl J. V. and Schulz, Marcel Holger and Simon, Martin}, LANGUAGE = {eng}, ISSN = {1340-2838; 1756-1663}, URL = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4535620&tool=pmcentrez&rendertype=abstract}, DOI = {10.1093/dnares/dsv014}, PUBLISHER = {Oxford University Press}, ADDRESS = {Oxford}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, DATE = {2015-08}, JOURNAL = {DNA Research: An International Journal for Rapid Publication of Reports on Genes and Genomes}, VOLUME = {22}, NUMBER = {4}, PAGES = {293--305}, }
Endnote
%0 Journal Article %A Cheaib, Miriam %A Dehghani Amirabad, Azim %A Nordström, Karl J. V. %A Schulz, Marcel Holger %A Simon, Martin %+ External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T Epigenetic regulation of serotype expression antagonizes transcriptome dynamics in Paramecium tetraurelia : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0028-52A5-D %F OTHER: accessionPMC4535620 %F OTHER: pmcidPMC4535620 %F OTHER: pmc-uid4535620 %R 10.1093/dnares/dsv014 %F OTHER: publisher-iddsv014 %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4535620&tool=pmcentrez&rendertype=abstract %2 PMC4535620 %7 2015-07-31 %D 2015 %K heat-shock %J DNA Research: An International Journal for Rapid Publication of Reports on Genes and Genomes %V 22 %N 4 %& 293 %P 293 - 305 %I Oxford University Press %C Oxford %@ false
36. Cijvat R, Manegold S, Kersten M, Klau GW, Schönhuth A, Marschall T, Zhang Y: Genome Sequence Analysis with MonetDB. Datenbank-Spektrum 2015, 15.
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@article{MarschallMonetDB15, TITLE = {Genome Sequence Analysis with {M}onet{DB}}, AUTHOR = {Cijvat, Robin and Manegold, Stefan and Kersten, Martin and Klau, Gunnar W. and Sch{\"o}nhuth, Alexander and Marschall, Tobias and Zhang, Ying}, LANGUAGE = {eng}, ISSN = {1618-2162}, DOI = {10.1007/s13222-015-0198-x}, PUBLISHER = {Springer}, ADDRESS = {Berlin}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, DATE = {2015}, JOURNAL = {Datenbank-Spektrum}, VOLUME = {15}, NUMBER = {3}, PAGES = {185--191}, }
Endnote
%0 Journal Article %A Cijvat, Robin %A Manegold, Stefan %A Kersten, Martin %A Klau, Gunnar W. %A Schönhuth, Alexander %A Marschall, Tobias %A Zhang, Ying %+ External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T Genome Sequence Analysis with MonetDB : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0029-5B50-E %R 10.1007/s13222-015-0198-x %7 2015-10-12 %D 2015 %J Datenbank-Spektrum %V 15 %N 3 %& 185 %P 185 - 191 %I Springer %C Berlin %@ false
37. Cijvat R, Manegold S, Kersten M, Klau GW, Schönhuth A, Marschall T, Zhang Y: Genome Sequence Analysis with MonetDB: A Case Study on Ebola. In Joint Workshop on Data Management for Science (DMS 2015); 2015.
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@inproceedings{CijvatDMforLS2015, TITLE = {Genome Sequence Analysis with {MonetDB}: A Case Study on {Ebola}virus diversity}, AUTHOR = {Cijvat, Robin and Manegold, Stefan and Kersten, Martin and Klau, Gunnar W. and Sch{\"o}nhuth, Alexander and Marschall, Tobias and Zhang, Ying}, LANGUAGE = {eng}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, BOOKTITLE = {Joint Workshop on Data Management for Science (DMS 2015)}, EDITOR = {Dorok, Sebastian and K{\"o}nig-Ries, Brigitta and Lange, Matthias and Rahm, Erhard and Saake, Gunter and Seeger, Bernhard}, ADDRESS = {Hamburg, Germany}, }
Endnote
%0 Conference Proceedings %A Cijvat, Robin %A Manegold, Stefan %A Kersten, Martin %A Klau, Gunnar W. %A Schönhuth, Alexander %A Marschall, Tobias %A Zhang, Ying %+ External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T Genome Sequence Analysis with MonetDB: A Case Study on Ebola : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0029-5E85-6 %D 2015 %B Joint Workshop on Data Management for Science %Z date of event: 2015-03-03 - 2015-03-03 %C Hamburg, Germany %B Joint Workshop on Data Management for Science %E Dorok, Sebastian; König-Ries, Brigitta; Lange, Matthias; Rahm, Erhard; Saake, Gunter; Seeger, Bernhard %U http://www.btw-2015.de/res/proceedings/Workshops/DMS/Cijvat-Genome_sequence_analysis_wi.pdf
38. Dietzen M, Kalinina OV, Taškova K, Kneissl B, Hildebrandt A-K, Jaenicke E, Decker H, Lengauer T, Hildebrandt A: Large Oligomeric Complex Structures Can Be Computationally Assembled by Efficiently Combining Docked Interfaces. Proteins: Structure, Function, and Bioinformatics 2015, 83.
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@article{Dietzenetal2015, TITLE = {Large Oligomeric Complex Structures Can Be Computationally Assembled by Efficiently Combining Docked Interfaces}, AUTHOR = {Dietzen, Matthias and Kalinina, Olga V. and Ta{\v s}kova, Katerina and Kneissl, Benny and Hildebrandt, Anna-Katharina and Jaenicke, Elmar and Decker, Heinz and Lengauer, Thomas and Hildebrandt, Andreas}, LANGUAGE = {eng}, ISSN = {0887-3585}, DOI = {10.1002/prot.24873}, PUBLISHER = {John Wiley \& Sons}, ADDRESS = {New York, NY}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, DATE = {2015}, JOURNAL = {Proteins: Structure, Function, and Bioinformatics}, VOLUME = {83}, NUMBER = {10}, PAGES = {1887--1899}, }
Endnote
%0 Journal Article %A Dietzen, Matthias %A Kalinina, Olga V. %A Taškova, Katerina %A Kneissl, Benny %A Hildebrandt, Anna-Katharina %A Jaenicke, Elmar %A Decker, Heinz %A Lengauer, Thomas %A Hildebrandt, Andreas %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T Large Oligomeric Complex Structures Can Be Computationally Assembled by Efficiently Combining Docked Interfaces : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0028-5273-E %R 10.1002/prot.24873 %7 2015 %D 2015 %J Proteins: Structure, Function, and Bioinformatics %V 83 %N 10 %& 1887 %P 1887 - 1899 %I John Wiley & Sons %C New York, NY %@ false
39. Döring M, Gasparoni G, Gries J, Nordström K, Lutsik P, Walter J, Pfeifer N: Identification and Analysis of Methylation Call Differences Between Bisulfite Microarray and Bisulfite Sequencing Data with Statistical Learning Techniques. BMC Bioinformatics (Proc ISCB 2014) 2015, 16(Suppl 3).
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@article{doering2015, TITLE = {Identification and Analysis of Methylation Call Differences Between Bisulfite Microarray and Bisulfite Sequencing Data with Statistical Learning Techniques}, AUTHOR = {D{\"o}ring, Matthias and Gasparoni, Gilles and Gries, Jasmin and Nordstr{\"o}m, Karl and Lutsik, Pavlo and Walter, J{\"o}rn and Pfeifer, Nico}, LANGUAGE = {eng}, ISSN = {1471-2105}, URL = {http://www.biomedcentral.com/1471-2105/16/S3/A7}, DOI = {10.1186/1471-2105-16-S3-A7}, PUBLISHER = {BioMed Central}, ADDRESS = {London}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, CONTENTS = {Background Methods Results Conclusion}, JOURNAL = {BMC Bioinformatics (Proc. ISCB)}, VOLUME = {16}, NUMBER = {Suppl 3}, EID = {A7}, BOOKTITLE = {Highlights from the Third International Society for Computational Biology (ISCB) European Student Council Symposium 2014}, }
Endnote
%0 Journal Article %A Döring, Matthias %A Gasparoni, Gilles %A Gries, Jasmin %A Nordström, Karl %A Lutsik, Pavlo %A Walter, Jörn %A Pfeifer, Nico %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Affiliation External Affiliation External Affiliation External Affiliation External Affiliation Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Identification and Analysis of Methylation Call Differences Between Bisulfite Microarray and Bisulfite Sequencing Data with Statistical Learning Techniques : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-C7F7-B %U http://www.biomedcentral.com/1471-2105/16/S3/A7 %R 10.1186/1471-2105-16-S3-A7 %7 2015-02-13 %D 2015 %8 13.02.2015 %Z Background Methods Results Conclusion %J BMC Bioinformatics %V 16 %N Suppl 3 %Z sequence number: A7 %I BioMed Central %C London %@ false %B Highlights from the Third International Society for Computational Biology (ISCB) European Student Council Symposium 2014 %O ISCB 2014
40. Ebert P, Müller F, Nordström K, Lengauer T, Schulz MH: A General Concept for Consistent Documentation of Computational Analyses. Database: The Journal of Biological Databases and Curation 2015, 2015.
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@article{EbertDatabase2015, TITLE = {A General Concept for Consistent Documentation of Computational Analyses}, AUTHOR = {Ebert, Peter and M{\"u}ller, Fabian and Nordstr{\"o}m, Karl and Lengauer, Thomas and Schulz, Marcel Holger}, LANGUAGE = {eng}, ISSN = {1758-0463}, URL = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4460408&tool=pmcentrez&rendertype=abstract}, DOI = {10.1093/database/bav050}, PUBLISHER = {Oxford University Press}, ADDRESS = {Oxford}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, JOURNAL = {Database: The Journal of Biological Databases and Curation}, VOLUME = {2015}, EID = {bav050}, }
Endnote
%0 Journal Article %A Ebert, Peter %A Müller, Fabian %A Nordström, Karl %A Lengauer, Thomas %A Schulz, Marcel Holger %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T A General Concept for Consistent Documentation of Computational Analyses : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0027-BD04-8 %F OTHER: accessionPMC4460408 %F OTHER: pmcidPMC4460408 %F OTHER: pmc-uid4460408 %R 10.1093/database/bav050 %F OTHER: publisher-idbav050 %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4460408&tool=pmcentrez&rendertype=abstract %7 2015-06-08 %D 2015 %8 08.06.2015 %J Database: The Journal of Biological Databases and Curation %V 2015 %Z sequence number: bav050 %I Oxford University Press %C Oxford %@ false
41. Ebert P, Bock C: Improving Reference Epigenome Catalogs by Computational Prediction. Nature Biotechnology 2015, 33.
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@article{Ebert2015, TITLE = {Improving Reference Epigenome Catalogs by Computational Prediction}, AUTHOR = {Ebert, Peter and Bock, Christoph}, LANGUAGE = {eng}, ISSN = {1087-0156}, DOI = {10.1038/nbt.3194}, PUBLISHER = {Nature Publishing Group}, ADDRESS = {New York, NY}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, DATE = {2015}, JOURNAL = {Nature Biotechnology}, VOLUME = {33}, NUMBER = {4}, PAGES = {354--355}, }
Endnote
%0 Journal Article %A Ebert, Peter %A Bock, Christoph %+ External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Improving Reference Epigenome Catalogs by Computational Prediction : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0026-C911-B %R 10.1038/nbt.3194 %7 2015-04-07 %D 2015 %J Nature Biotechnology %V 33 %N 4 %& 354 %P 354 - 355 %I Nature Publishing Group %C New York, NY %@ false
42. Farlik M, Sheffield NC, Nuzzo A, Datlinger P, Schönegger A, Klughammer J, Bock C: Single-Cell DNA Methylome Sequencing and Bioinformatic Inference of Epigenomic Cell-State Dynamics. Cell Reports 2015, 10.
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@article{BockCellReports2015, TITLE = {Single-Cell {DNA} Methylome Sequencing and Bioinformatic Inference of Epigenomic Cell-State Dynamics}, AUTHOR = {Farlik, Matthias and Sheffield, Nathan C. and Nuzzo, Angelo and Datlinger, Paul and Sch{\"o}negger, Andreas and Klughammer, Johanna and Bock, Christoph}, LANGUAGE = {eng}, DOI = {10.1016/j.celrep.2015.02.001}, PUBLISHER = {Elsevier}, ADDRESS = {Amsterdam}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, JOURNAL = {Cell Reports}, VOLUME = {10}, NUMBER = {8}, PAGES = {1386--1397}, }
Endnote
%0 Journal Article %A Farlik, Matthias %A Sheffield, Nathan C. %A Nuzzo, Angelo %A Datlinger, Paul %A Schönegger, Andreas %A Klughammer, Johanna %A Bock, Christoph %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Single-Cell DNA Methylome Sequencing and Bioinformatic Inference of Epigenomic Cell-State Dynamics : %! Single-Cell {DNA} Methylome Sequencing and Bioinformatic Inference of Epigenomic Cell-State Dynamics %G eng %U http://hdl.handle.net/11858/00-001M-0000-0026-BEE0-5 %R 10.1016/j.celrep.2015.02.001 %7 2015 %D 2015 %J Cell Reports %V 10 %N 8 %& 1386 %P 1386 - 1397 %I Elsevier %C Amsterdam %U http://www.sciencedirect.com/science/article/pii/S2211124715001096
43. Fink T, Wolf A, Maurer F, Albrecht FW, Heim N, Wolf B, Hauschild AC, Bödeker B, Baumbach JI, Volk T, Sessler DI, Kreuer S: Volatile Organic Compounds during Inflammation and Sepsis in Rats: A Potential Breath Test Using Ion-mobility Spectrometry. Anesthesiology 2015, 122.
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@article{BaumbachVolatile2015, TITLE = {Volatile Organic Compounds during Inflammation and Sepsis in Rats: {A} Potential Breath Test Using Ion-mobility Spectrometry}, AUTHOR = {Fink, Tobias and Wolf, Alexander and Maurer, Felix and Albrecht, Frederic W. and Heim, Nathalie and Wolf, Beate and Hauschild, Anne C. and B{\"o}deker, Bertram and Baumbach, J{\"o}rg I. and Volk, Thomas and Sessler, Daniel I. and Kreuer, Sascha}, LANGUAGE = {eng}, ISSN = {0003-3022}, DOI = {10.1097/ALN.0000000000000420}, PUBLISHER = {American Society of Anesthesiologists}, ADDRESS = {Philadelphia, Pa.}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, DATE = {2015}, JOURNAL = {Anesthesiology}, VOLUME = {122}, NUMBER = {1}, PAGES = {117--126}, }
Endnote
%0 Journal Article %A Fink, Tobias %A Wolf, Alexander %A Maurer, Felix %A Albrecht, Frederic W. %A Heim, Nathalie %A Wolf, Beate %A Hauschild, Anne C. %A Bödeker, Bertram %A Baumbach, Jörg I. %A Volk, Thomas %A Sessler, Daniel I. %A Kreuer, Sascha %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations %T Volatile Organic Compounds during Inflammation and Sepsis in Rats: A Potential Breath Test Using Ion-mobility Spectrometry : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0026-BF4B-2 %R 10.1097/ALN.0000000000000420 %7 2015 %D 2015 %J Anesthesiology %V 122 %N 1 %& 117 %P 117 - 126 %I American Society of Anesthesiologists %C Philadelphia, Pa. %@ false
44. Garg S: Towards Fewer Seeds for Network Discovery. In Modelling, Computation and Optimization in Information Systems and Management Sciences (MCO 2015). Springer; 2015. [Advances in Intelligent Systems and Computing, vol. 360]
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@inproceedings{GargMCO2015, TITLE = {Towards Fewer Seeds for Network Discovery}, AUTHOR = {Garg, Shilpa}, LANGUAGE = {eng}, ISSN = {2194-5357}, ISBN = {978-3-319-18166-0}, DOI = {10.1007/978-3-319-18167-7_8}, PUBLISHER = {Springer}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, DATE = {2015}, BOOKTITLE = {Modelling, Computation and Optimization in Information Systems and Management Sciences (MCO 2015)}, EDITOR = {Thi, Hoai An Le and Dinh, Tao Pham and Nguyen, Ngoc Thanh}, PAGES = {81--89}, SERIES = {Advances in Intelligent Systems and Computing}, VOLUME = {360}, ADDRESS = {Metz, France}, }
Endnote
%0 Conference Proceedings %A Garg, Shilpa %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Towards Fewer Seeds for Network Discovery : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002A-FC95-E %R 10.1007/978-3-319-18167-7_8 %D 2015 %B 3rd International Conference on Modelling, Computation and Optimization in Information Systems and Management Sciences %Z date of event: 2015-05-11 - 2015-05-13 %C Metz, France %B Modelling, Computation and Optimization in Information Systems and Management Sciences %E Thi, Hoai An Le; Dinh, Tao Pham; Nguyen, Ngoc Thanh %P 81 - 89 %I Springer %@ 978-3-319-18166-0 %B Advances in Intelligent Systems and Computing %N 360 %@ false
45. Grund S, Gkioule C, Termos T, Pfeifer N, Kobbe G, Verheyen J, Adams O: Primarily Oseltamivir-resistant Influenza A (H1N1pdm09) Virus Evolving into a Multidrug-resistant Virus Carrying H275Y and I223R Neuraminidase Substitutions. Antiviral Therapy 2015, 20.
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@article{Grund2015, TITLE = {Primarily Oseltamivir-resistant Influenza {A} ({H1N1pdm09}) Virus Evolving into a Multidrug-resistant Virus Carrying {H275Y} and {I223R} Neuraminidase Substitutions}, AUTHOR = {Grund, Sebastian and Gkioule, Charikleia and Termos, Tahani and Pfeifer, Nico and Kobbe, Guido and Verheyen, Jens and Adams, Ortwin}, LANGUAGE = {eng}, ISSN = {1359-6535}, DOI = {10.3851/IMP2811}, PUBLISHER = {International Medical Press}, ADDRESS = {London}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, DATE = {2015}, JOURNAL = {Antiviral Therapy}, VOLUME = {20}, PAGES = {97--100}, }
Endnote
%0 Journal Article %A Grund, Sebastian %A Gkioule, Charikleia %A Termos, Tahani %A Pfeifer, Nico %A Kobbe, Guido %A Verheyen, Jens %A Adams, Ortwin %+ External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations %T Primarily Oseltamivir-resistant Influenza A (H1N1pdm09) Virus Evolving into a Multidrug-resistant Virus Carrying H275Y and I223R Neuraminidase Substitutions : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0028-5380-8 %R 10.3851/IMP2811 %7 2015 %D 2015 %J Antiviral Therapy %V 20 %& 97 %P 97 - 100 %I International Medical Press %C London %@ false
46. Hauschild A-C, Maurer F, Fink T, Baumbach JI, Kreuer S, Eckel SP, Baumbach J: Analysis of Volatile Organic Compounds during Sepsis in Rats. In Metaboliten in Prozessabluft und Ausatemluft; 2015.
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@inproceedings{HauschildMetaboliten2015, TITLE = {Analysis of Volatile Organic Compounds during Sepsis in Rats}, AUTHOR = {Hauschild, Anne-Christin and Maurer, Felix and Fink, Tobias and Baumbach, J{\"o}rg Ingo and Kreuer, Sascha and Eckel, Sandrah P. and Baumbach, Jan}, LANGUAGE = {eng}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, BOOKTITLE = {Metaboliten in Prozessabluft und Ausatemluft}, PAGES = {23--23}, ADDRESS = {Reutlingen, Germany}, }
Endnote
%0 Conference Proceedings %A Hauschild, Anne-Christin %A Maurer, Felix %A Fink, Tobias %A Baumbach, Jörg Ingo %A Kreuer, Sascha %A Eckel, Sandrah P. %A Baumbach, Jan %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations %T Analysis of Volatile Organic Compounds during Sepsis in Rats : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002A-06C9-B %D 2015 %B 6. Symposium Metaboliten in Prozessabluft und Ausatemluft %Z date of event: 2015-09-22 - 2015-09-23 %C Reutlingen, Germany %B Metaboliten in Prozessabluft und Ausatemluft %P 23 - 23 %U http://www.bs-analytik.de/pdf/150508_BoA_Anwedertreffen_v5.pdf
47. Hauschild A-C, Frisch T, Baumbach JI, Baumbach J: Carotta: Revealing Hidden Confounder Markers in Metabolic Breath Profiles. Metabolites 2015, 5.
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@article{HauschildMetabolites2015, TITLE = {Carotta: {R}evealing Hidden Confounder Markers in Metabolic Breath Profiles}, AUTHOR = {Hauschild, Anne-Christin and Frisch, Tobias and Baumbach, J{\"o}rg Ingo and Baumbach, Jan}, LANGUAGE = {eng}, ISSN = {2218-1989}, URL = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4495376&tool=pmcentrez&rendertype=abstract}, DOI = {10.3390/metabo5020344}, PUBLISHER = {MDPI}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, JOURNAL = {Metabolites}, VOLUME = {5}, NUMBER = {2}, PAGES = {344--363}, }
Endnote
%0 Journal Article %A Hauschild, Anne-Christin %A Frisch, Tobias %A Baumbach, Jörg Ingo %A Baumbach, Jan %A contributor: Kaleta, Christoph %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations %T Carotta: Revealing Hidden Confounder Markers in Metabolic Breath Profiles : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0028-1B69-D %F OTHER: accessionPMC4495376 %F OTHER: pmcidPMC4495376 %F OTHER: pmc-uid4495376 %R 10.3390/metabo5020344 %F OTHER: publisher-idmetabolites-05-00344 %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4495376&tool=pmcentrez&rendertype=abstract %7 2015-06-10 %D 2015 %8 10.06.2015 %K breath analysis %J Metabolites %V 5 %N 2 %& 344 %P 344 - 363 %I MDPI %@ false
48. Hauschild A-C, Baumbach JI, Baumbach J: Bioinformatics Methods for Breath Analysis and Biomarker Detection. In Breath Research Topics from IABR 2015 Summit; 2015.
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@inproceedings{HauschildIABR2015, TITLE = {Bioinformatics Methods for Breath Analysis and Biomarker Detection}, AUTHOR = {Hauschild, Anne-Christin and Baumbach, J{\"o}rg Ingo and Baumbach, Jan}, LANGUAGE = {eng}, URL = {http://respiratoryresearch.com/breath-research-topics-from-iabr-2015-summit/}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, BOOKTITLE = {Breath Research Topics from IABR 2015 Summit}, EDITOR = {Baddour, Rafid}, ADDRESS = {Vienna, Austria}, }
Endnote
%0 Conference Proceedings %A Hauschild, Anne-Christin %A Baumbach, Jörg Ingo %A Baumbach, Jan %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Bioinformatics Methods for Breath Analysis and Biomarker Detection : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002A-14B6-6 %U http://respiratoryresearch.com/breath-research-topics-from-iabr-2015-summit/ %D 2015 %B International Association of Breath Researchers 2015 Summit Conference %Z date of event: 2015-09-14 - 2015-09-16 %C Vienna, Austria %B Breath Research Topics from IABR 2015 Summit %E Baddour, Rafid
49. He X, Cicek AE, Wang Y, Schulz MH, Le H-S, Bar-Joseph Z: De Novo ChIP-seq Analysis. Genome Biology 2015, 16.
Abstract
ABSTRACT: Methods for the analysis of chromatin immunoprecipitation sequencing (ChIP-seq) data start by aligning the short reads to a reference genome. While often successful, they are not appropriate for cases where a reference genome is not available. Here we develop methods for de novo analysis of ChIP-seq data. Our methods combine de novo assembly with statistical tests enabling motif discovery without the use of a reference genome. We validate the performance of our method using human and mouse data. Analysis of fly data indicates that our method outperforms alignment based methods that utilize closely related species.
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@article{He2015, TITLE = {De novo {ChIP}-seq analysis}, AUTHOR = {He, Xin and Cicek, A. Ercument and Wang, Yuhao and Schulz, Marcel H. and Le, Hai-Son and Bar-Joseph, Ziv}, LANGUAGE = {eng}, ISSN = {1474-760X}, DOI = {10.1186/s13059-015-0756-4}, PUBLISHER = {BioMed Central Ltd.}, ADDRESS = {London}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, ABSTRACT = {ABSTRACT: Methods for the analysis of chromatin immunoprecipitation sequencing (ChIP-seq) data start by aligning the short reads to a reference genome. While often successful, they are not appropriate for cases where a reference genome is not available. Here we develop methods for de novo analysis of ChIP-seq data. Our methods combine de novo assembly with statistical tests enabling motif discovery without the use of a reference genome. We validate the performance of our method using human and mouse data. Analysis of fly data indicates that our method outperforms alignment based methods that utilize closely related species.}, JOURNAL = {Genome Biology}, VOLUME = {16}, NUMBER = {1}, EID = {205}, }
Endnote
%0 Journal Article %A He, Xin %A Cicek, A. Ercument %A Wang, Yuhao %A Schulz, Marcel H. %A Le, Hai-Son %A Bar-Joseph, Ziv %+ External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations %T De Novo ChIP-seq Analysis : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0028-DD0C-3 %R 10.1186/s13059-015-0756-4 %7 2015-09-23 %D 2015 %8 23.09.2015 %X ABSTRACT: Methods for the analysis of chromatin immunoprecipitation sequencing (ChIP-seq) data start by aligning the short reads to a reference genome. While often successful, they are not appropriate for cases where a reference genome is not available. Here we develop methods for de novo analysis of ChIP-seq data. Our methods combine de novo assembly with statistical tests enabling motif discovery without the use of a reference genome. We validate the performance of our method using human and mouse data. Analysis of fly data indicates that our method outperforms alignment based methods that utilize closely related species. %J Genome Biology %V 16 %N 1 %Z sequence number: 205 %I BioMed Central Ltd. %C London %@ false %U http://www.genomebiology.com/2015/16/1/205
50. Karp PD, Berger B, Kovats D, Lengauer T, Linial M, Sabeti P, Hide W, Rost B: ISCB Ebola Award for Important Future Research on the Computational Biology of Ebola Virus. F1000Research 2015, 4.
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@article{LengauerF1000Research2015, TITLE = {{ISCB Ebola Award} for Important Future Research on the Computational Biology of {Ebola} Virus}, AUTHOR = {Karp, Peter D. and Berger, Bonnie and Kovats, Diane and Lengauer, Thomas and Linial, Michal and Sabeti, Pardis and Hide, Winston and Rost, Burkhard}, LANGUAGE = {eng}, ISSN = {2046-1402}, URL = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4457108&tool=pmcentrez&rendertype=abstract}, DOI = {10.12688/f1000research.6038.1}, PUBLISHER = {F1000Research}, ADDRESS = {London, UK}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, JOURNAL = {F1000Research}, VOLUME = {4}, EID = {12}, }
Endnote
%0 Journal Article %A Karp, Peter D. %A Berger, Bonnie %A Kovats, Diane %A Lengauer, Thomas %A Linial, Michal %A Sabeti, Pardis %A Hide, Winston %A Rost, Burkhard %+ External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations %T ISCB Ebola Award for Important Future Research on the Computational Biology of Ebola Virus : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0027-BD0D-5 %F OTHER: accessionPMC4457108 %F OTHER: pmcidPMC4457108 %F OTHER: pmc-uid4457108 %R 10.12688/f1000research.6038.1 %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4457108&tool=pmcentrez&rendertype=abstract %7 2015-01-15 %D 2015 %8 15.01.2015 %J F1000Research %V 4 %Z sequence number: 12 %I F1000Research %C London, UK %@ false
51. Karp PD, Berger B, Kovats D, Lengauer T, Linial M, Sabeti P, Hide W, Rost B: Message from the ISCB: ISCB Ebola award for important future research on the computational biology of Ebola virus. Bioinformatics 2015, 31.
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@article{LengauerBioinformatics2015, TITLE = {Message from the {ISCB}: {ISCB} {Ebola} award for important future research on the computational biology of {Ebola} virus}, AUTHOR = {Karp, Peter D. and Berger, Bonnie and Kovats, Diane and Lengauer, Thomas and Linial, Michal and Sabeti, Pardis and Hide, Winston and Rost, Burkhard}, ISSN = {1367-4803}, DOI = {10.1093/bioinformatics/btv019}, PUBLISHER = {Oxford University Press}, ADDRESS = {Oxford}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, DATE = {2015}, JOURNAL = {Bioinformatics}, VOLUME = {31}, NUMBER = {4}, PAGES = {616--617}, }
Endnote
%0 Journal Article %A Karp, Peter D. %A Berger, Bonnie %A Kovats, Diane %A Lengauer, Thomas %A Linial, Michal %A Sabeti, Pardis %A Hide, Winston %A Rost, Burkhard %+ external external external Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society external external external external %T Message from the ISCB: ISCB Ebola award for important future research on the computational biology of Ebola virus : %U http://hdl.handle.net/11858/00-001M-0000-0026-A0E1-3 %F ISI: 000350059600029 %R 10.1093/bioinformatics/btv019 %D 2015 %J Bioinformatics %V 31 %N 4 %& 616 %P 616 - 617 %I Oxford University Press %C Oxford %@ false
52. Karp PD, Berger B, Kovats D, Lengauer T, Linial M, Sabeti P, Hide W, Rost B: ISCB Ebola Award for Important Future Research on the Computational Biology of Ebola Virus. PLoS Computational Biology 2015, 11.
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@article{KarpPLoS2015, TITLE = {{ISCB} {Ebola Award} for Important Future Research on the Computational Biology of {E}bola Virus}, AUTHOR = {Karp, Peter D. and Berger, Bonnie and Kovats, Diane and Lengauer, Thomas and Linial, Michal and Sabeti, Pardis and Hide, Winston and Rost, Burkhard}, LANGUAGE = {eng}, ISSN = {1553-734X; 1553-7358}, URL = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4310586&tool=pmcentrez&rendertype=abstract}, DOI = {10.1371/journal.pcbi.1004087}, PUBLISHER = {Public Library of Science}, ADDRESS = {San Francisco, CA}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, JOURNAL = {PLoS Computational Biology}, VOLUME = {11}, NUMBER = {1}, EID = {e1004087}, }
Endnote
%0 Journal Article %A Karp, Peter D. %A Berger, Bonnie %A Kovats, Diane %A Lengauer, Thomas %A Linial, Michal %A Sabeti, Pardis %A Hide, Winston %A Rost, Burkhard %+ External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations %T ISCB Ebola Award for Important Future Research on the Computational Biology of Ebola Virus : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-E54D-E %2 PMC4310586 %F OTHER: publisher-idPCOMPBIOL-D-14-02242 %R 10.1371/journal.pcbi.1004087 %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4310586&tool=pmcentrez&rendertype=abstract %7 2015-01-29 %D 2015 %8 29.01.2015 %J PLoS Computational Biology %V 11 %N 1 %Z sequence number: e1004087 %I Public Library of Science %C San Francisco, CA %@ false
53. Klughammer J, Datlinger P, Printz D, Sheffield NC, Farlik M, Hadler J, Fritsch G, Bock C: Differential DNA Methylation Analysis without a Reference Genome. Cell 2015, 11.
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@article{Klughammer2015, TITLE = {Differential {DNA} Methylation Analysis without a Reference Genome}, AUTHOR = {Klughammer, Johanna and Datlinger, Paul and Printz, Dieter and Sheffield, Nathan C. and Farlik, Matthias and Hadler, Johanna and Fritsch, Gerhard and Bock, Christoph}, LANGUAGE = {eng}, ISSN = {0092-8674}, DOI = {10.1016/j.celrep.2015.11.024}, PUBLISHER = {Cell Press}, ADDRESS = {Cambridge, Mass.}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, DATE = {2015}, JOURNAL = {Cell}, VOLUME = {11}, PAGES = {2621--2633}, }
Endnote
%0 Journal Article %A Klughammer, Johanna %A Datlinger, Paul %A Printz, Dieter %A Sheffield, Nathan C. %A Farlik, Matthias %A Hadler, Johanna %A Fritsch, Gerhard %A Bock, Christoph %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Differential DNA Methylation Analysis without a Reference Genome : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0029-5762-8 %R 10.1016/j.celrep.2015.11.024 %7 2015 %D 2015 %J Cell %V 11 %& 2621 %P 2621 - 2633 %I Cell Press %C Cambridge, Mass. %@ false %U http://www.sciencedirect.com/science/article/pii/S2211124715013248
54. Kouri V, Khouri R, Alemán Y, Abrahantes Y, Vercauteren J, Pineda-Peña A-C, Theys K, Megens S, Moutschen M, Pfeifer N, Van Weyenbergh J, Pérez AB, Pérez J, Pérez L, Van Laethem K, Vandamme A-M: CRF19_cpx is an Evolutionary Fit HIV-1 Variant Strongly Associated With Rapid Progression to AIDS in Cuba. EBioMedicine 2015, 2.
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@article{Kouri2015, TITLE = {{CRF19}{\textunderscore}cpx is an Evolutionary Fit {HIV}-1 Variant Strongly Associated With Rapid Progression to {AIDS} in Cuba}, AUTHOR = {Kouri, Vivian and Khouri, Ricardo and Alem{\'a}n, Yoan and Abrahantes, Yeissel and Vercauteren, Jurgen and Pineda-Pe{\~n}a, Andrea-Clemencia and Theys, Kristof and Megens, Sarah and Moutschen, Michel and Pfeifer, Nico and Van Weyenbergh, Johan and P{\'e}rez, Ana B. and P{\'e}rez, Jorge and P{\'e}rez, Lissette and Van Laethem, Kristel and Vandamme, Anne-Mieke}, LANGUAGE = {eng}, URL = {http://www.ebiomedicine.com/article/S2352-3964(15)00038-9/abstract}, DOI = {10.1016/j.ebiom.2015.01.015}, PUBLISHER = {Elsevier}, ADDRESS = {Amsterdam}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, JOURNAL = {EBioMedicine}, VOLUME = {2}, NUMBER = {3}, PAGES = {244--254}, }
Endnote
%0 Journal Article %A Kouri, Vivian %A Khouri, Ricardo %A Alemán, Yoan %A Abrahantes, Yeissel %A Vercauteren, Jurgen %A Pineda-Peña, Andrea-Clemencia %A Theys, Kristof %A Megens, Sarah %A Moutschen, Michel %A Pfeifer, Nico %A Van Weyenbergh, Johan %A Pérez, Ana B. %A Pérez, Jorge %A Pérez, Lissette %A Van Laethem, Kristel %A Vandamme, Anne-Mieke %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations %T CRF19_cpx is an Evolutionary Fit HIV-1 Variant Strongly Associated With Rapid Progression to AIDS in Cuba : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-D01E-C %U http://www.ebiomedicine.com/article/S2352-3964(15)00038-9/abstract %R 10.1016/j.ebiom.2015.01.015 %7 2015-01-28 %D 2015 %8 28.01.2015 %J EBioMedicine %V 2 %N 3 %& 244 %P 244 - 254 %I Elsevier %C Amsterdam %U http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4484819/pdf/main.pdf
55. Lawyer G: Understanding the Influence of All Nodes in a Network. Scientific Reports 2015, 5.
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@article{Lawyer2015, TITLE = {Understanding the Influence of All Nodes in a Network}, AUTHOR = {Lawyer, Glenn}, LANGUAGE = {eng}, DOI = {10.1038/srep08665}, PUBLISHER = {Nature Publishing Group}, ADDRESS = {London, UK}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, JOURNAL = {Scientific Reports}, VOLUME = {5}, EID = {8665}, }
Endnote
%0 Journal Article %A Lawyer, Glenn %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Understanding the Influence of All Nodes in a Network : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-CAA9-3 %R 10.1038/srep08665 %7 2015-03-02 %D 2015 %8 02.03.2015 %J Scientific Reports %O Sci. Rep. %V 5 %Z sequence number: 8665 %I Nature Publishing Group %C London, UK
56. Lengauer T, Nussinov R: How to Write a Presubmission Inquiry. PLoS Computational Biology 2015, 11.
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@article{LengauerNussinov2015, TITLE = {How to Write a Presubmission Inquiry}, AUTHOR = {Lengauer, Thomas and Nussinov, Ruth}, LANGUAGE = {eng}, ISSN = {1553-734X}, DOI = {10.1371/journal.pcbi.1004098}, PUBLISHER = {Public Library of Science}, ADDRESS = {San Francisco, CA}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, JOURNAL = {PLoS Computational Biology}, VOLUME = {11}, NUMBER = {2}, EID = {e1004098}, }
Endnote
%0 Journal Article %A Lengauer, Thomas %A Nussinov, Ruth %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T How to Write a Presubmission Inquiry : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0026-C655-D %R 10.1371/journal.pcbi.1004098 %7 2015-02-26 %D 2015 %8 26.02.2015 %J PLoS Computational Biology %V 11 %N 2 %Z sequence number: e1004098 %I Public Library of Science %C San Francisco, CA %@ false %U http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004098
57. Leung WY, Marschall T, Paudel Y, Falquet L, Mei H, Schönhuth A, Maoz (Moss) TY: SV-AUTOPILOT: Optimized, Automated Construction of Structural Variation Discovery and Benchmarking Pipelines. BMC Genomics 2015, 16.
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@article{Marschall2015, TITLE = {SV-AUTOPILOT: {O}ptimized, Automated Construction of Structural Variation Discovery and Benchmarking Pipelines}, AUTHOR = {Leung, Wai Yi and Marschall, Tobias and Paudel, Yogesh and Falquet, Laurent and Mei, Hailiang and Sch{\"o}nhuth, Alexander and Maoz (Moss), Tiffanie Yael}, LANGUAGE = {eng}, ISSN = {1471-2164}, URL = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4520269&tool=pmcentrez&rendertype=abstract}, DOI = {10.1186/s12864-015-1376-9}, PUBLISHER = {BioMed Central}, ADDRESS = {London}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, JOURNAL = {BMC Genomics}, VOLUME = {16}, NUMBER = {1}, EID = {238}, }
Endnote
%0 Journal Article %A Leung, Wai Yi %A Marschall, Tobias %A Paudel, Yogesh %A Falquet, Laurent %A Mei, Hailiang %A Schönhuth, Alexander %A Maoz (Moss), Tiffanie Yael %+ External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations %T SV-AUTOPILOT: Optimized, Automated Construction of Structural Variation Discovery and Benchmarking Pipelines : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0028-1B8C-0 %F OTHER: accessionPMC4520269 %F OTHER: pmcidPMC4520269 %F OTHER: pmc-uid4520269 %F OTHER: publisher-id1376 %R 10.1186/s12864-015-1376-9 %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4520269&tool=pmcentrez&rendertype=abstract %7 2015-03-25 %D 2015 %8 25.03.2015 %K SV tool development %J BMC Genomics %V 16 %N 1 %Z sequence number: 238 %I BioMed Central %C London %@ false
58. Lübke N, Di Cristanziano V, Sierra S, Knops E, Schülter E, Jensen B, Oette M, Lengauer T, Kaiser R: Proviral DNA as a Target for HIV-1 Resistance Analysis. Intervirology 2015, 58.
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@article{Lubke2015, TITLE = {Proviral {DNA} as a Target for {HIV}-1 Resistance Analysis}, AUTHOR = {L{\"u}bke, Nadine and Di Cristanziano, Veronica and Sierra, Saleta and Knops, Elena and Sch{\"u}lter, Eugen and Jensen, Bj{\"o}rn and Oette, Mark and Lengauer, Thomas and Kaiser, Rolf}, LANGUAGE = {eng}, DOI = {10.1159/000431093}, PUBLISHER = {Karger}, ADDRESS = {Basel}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, DATE = {2015}, JOURNAL = {Intervirology}, VOLUME = {58}, NUMBER = {3}, PAGES = {184--189}, }
Endnote
%0 Journal Article %A Lübke, Nadine %A Di Cristanziano, Veronica %A Sierra, Saleta %A Knops, Elena %A Schülter, Eugen %A Jensen, Björn %A Oette, Mark %A Lengauer, Thomas %A Kaiser, Rolf %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T Proviral DNA as a Target for HIV-1 Resistance Analysis : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0028-5373-6 %R 10.1159/000431093 %7 2015 %D 2015 %K Kaiser, Rolf %J Intervirology %V 58 %N 3 %& 184 %P 184 - 189 %I Karger %C Basel
59. Mueller SC, Backes C, Kalinina OV, Meder B, Stöckel D, Lenhof H-P, Meese E, Keller A: BALL-SNP: Combining Genetic and Structural Information to Identify Candidate non-Synonymous Single Nucleotide Polymorphisms. Genome Medicine 2015, 7.
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@article{KalininaGenomeMed2015, TITLE = {{BALL}-{SNP}: {C}ombining Genetic and Structural Information to Identify Candidate non-Synonymous Single Nucleotide Polymorphisms}, AUTHOR = {Mueller, Sabine C. and Backes, Christina and Kalinina, Olga V. and Meder, Benjamin and St{\"o}ckel, Daniel and Lenhof, Hans-Peter and Meese, Eckart and Keller, Andreas}, LANGUAGE = {eng}, ISSN = {1756-994X}, URL = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4506604&tool=pmcentrez&rendertype=abstract}, DOI = {10.1186/s13073-015-0190-y}, PUBLISHER = {BioMed Central}, ADDRESS = {London}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, JOURNAL = {Genome Medicine}, VOLUME = {7}, NUMBER = {1}, EID = {65}, }
Endnote
%0 Journal Article %A Mueller, Sabine C. %A Backes, Christina %A Kalinina, Olga V. %A Meder, Benjamin %A Stöckel, Daniel %A Lenhof, Hans-Peter %A Meese, Eckart %A Keller, Andreas %+ External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations %T BALL-SNP: Combining Genetic and Structural Information to Identify Candidate non-Synonymous Single Nucleotide Polymorphisms : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0028-1B2E-4 %F OTHER: accessionPMC4506604 %F OTHER: pmcidPMC4506604 %F OTHER: pmc-uid4506604 %F OTHER: publisher-id190 %R 10.1186/s13073-015-0190-y %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4506604&tool=pmcentrez&rendertype=abstract %7 2015-07-01 %D 2015 %8 01.07.2015 %J Genome Medicine %V 7 %N 1 %Z sequence number: 65 %I BioMed Central %C London %@ false
60. Patterson M, Marschall T, Pisanti N, Iersel L, Stougie L, Klau GW, Schönhuth A: WhatsHap: Weighted Haplotype Assembly for Future-Generation Sequencing Reads. Journal of Computational Biology 2015, 22:498–509.
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@article{Patterson2015, TITLE = {{WhatsHap}: {W}eighted Haplotype Assembly for Future-Generation Sequencing Reads}, AUTHOR = {Patterson, Murray and Marschall, Tobias and Pisanti, Nadia and Iersel, Leo and Stougie, Leen and Klau, Gunnar W. and Sch{\"o}nhuth, Alexander}, LANGUAGE = {eng}, ISSN = {1066-5277}, DOI = {10.1089/cmb.2014.0157}, PUBLISHER = {Mary Ann Liebert}, ADDRESS = {New York, NY}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, DATE = {2015}, JOURNAL = {Journal of Computational Biology}, VOLUME = {22}, NUMBER = {6}, PAGES = {498--509}, }
Endnote
%0 Journal Article %A Patterson, Murray %A Marschall, Tobias %A Pisanti, Nadia %A Iersel, Leo %A Stougie, Leen %A Klau, Gunnar W. %A Schönhuth, Alexander %+ External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations %T WhatsHap: Weighted Haplotype Assembly for Future-Generation Sequencing Reads : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0029-1A80-E %R 10.1089/cmb.2014.0157 %7 2015 %D 2015 %J Journal of Computational Biology %V 22 %N 6 %& 498 %P 498 - 509 %I Mary Ann Liebert %C New York, NY %@ false
61. Pironti A, Sierra S, Kaiser R, Lengauer T, Pfeifer N: Effects of Sequence Alterations on Results from Genotypic Tropism Testing. Journal of Clinical Virology 2015, 65.
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@article{Pironti2015, TITLE = {Effects of Sequence Alterations on Results from Genotypic Tropism Testing}, AUTHOR = {Pironti, Alejandro and Sierra, Saleta and Kaiser, Rolf and Lengauer, Thomas and Pfeifer, Nico}, LANGUAGE = {eng}, ISSN = {1386-6532}, DOI = {10.1016/j.jcv.2015.02.006}, PUBLISHER = {Elsevier}, ADDRESS = {Amsterdam}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, JOURNAL = {Journal of Clinical Virology}, VOLUME = {65}, PAGES = {68--73}, }
Endnote
%0 Journal Article %A Pironti, Alejandro %A Sierra, Saleta %A Kaiser, Rolf %A Lengauer, Thomas %A Pfeifer, Nico %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Effects of Sequence Alterations on Results from Genotypic Tropism Testing : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-CFA4-1 %R 10.1016/j.jcv.2015.02.006 %7 2015-02-10 %D 2015 %8 10.02.2015 %J Journal of Clinical Virology %V 65 %& 68 %P 68 - 73 %I Elsevier %C Amsterdam %@ false
62. Poenisch M, Metz P, Blankenburg H, Ruggieri A, Lee J-Y, Rupp D, Rebhan I, Diederich K, Kaderali L, Domingues FS, Albrecht M, Lohmann V, Erfle H, Bartenschlager R: Identification of HNRNPK as Regulator of Hepatitis C Virus Particle Production. PLoS Pathogens 2015, 11.
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@article{PoenischPLoSPathog2015, TITLE = {Identification of {HNRNPK} as Regulator of Hepatitis {C} Virus Particle Production}, AUTHOR = {Poenisch, Marion and Metz, Philippe and Blankenburg, Hagen and Ruggieri, Alessia and Lee, Ji-Young and Rupp, Daniel and Rebhan, Ilka and Diederich, Kathrin and Kaderali, Lars and Domingues, Francisco S. and Albrecht, Mario and Lohmann, Volker and Erfle, Holger and Bartenschlager, Ralf}, LANGUAGE = {eng}, ISSN = {1553-7366; 1553-7374}, URL = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4287573&tool=pmcentrez&rendertype=abstract}, DOI = {10.1371/journal.ppat.1004573}, PUBLISHER = {Public Library of Science}, ADDRESS = {San Francisco, CA}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, JOURNAL = {PLoS Pathogens}, VOLUME = {11}, NUMBER = {1}, EID = {e1004573}, }
Endnote
%0 Journal Article %A Poenisch, Marion %A Metz, Philippe %A Blankenburg, Hagen %A Ruggieri, Alessia %A Lee, Ji-Young %A Rupp, Daniel %A Rebhan, Ilka %A Diederich, Kathrin %A Kaderali, Lars %A Domingues, Francisco S. %A Albrecht, Mario %A Lohmann, Volker %A Erfle, Holger %A Bartenschlager, Ralf %A contributor: Randall, Glenn %+ External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations %T Identification of HNRNPK as Regulator of Hepatitis C Virus Particle Production : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-9075-F %F OTHER: accessionPMC4287573 %F OTHER: pmcidPMC4287573 %F OTHER: pmc-uid4287573 %F OTHER: publisher-idPPATHOGENS-D-14-01626 %R 10.1371/journal.ppat.1004573 %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4287573&tool=pmcentrez&rendertype=abstract %7 2015-01-08 %D 2015 %8 08.01.2015 %J PLoS Pathogens %V 11 %N 1 %Z sequence number: e1004573 %I Public Library of Science %C San Francisco, CA %@ false
63. Pohlmann T, Baumann S, Haag C, Albrecht M, Feldbrügge M: A FYVE Zinc Finger Domain Protein Specifically Links mRNA Transport to Endosome Trafficking. eLife 2015.
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@article{Pohlmann2015, TITLE = {A {FYVE} Zinc Finger Domain Protein Specifically Links {mRNA} Transport to Endosome Trafficking}, AUTHOR = {Pohlmann, Thomas and Baumann, Sebastian and Haag, Carl and Albrecht, Mario and Feldbr{\"u}gge, Michael}, LANGUAGE = {eng}, DOI = {10.7554/eLife.06041}, PUBLISHER = {eLife Sciences Publications}, ADDRESS = {Cambridge}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, JOURNAL = {eLife}, EID = {e06041}, }
Endnote
%0 Journal Article %A Pohlmann, Thomas %A Baumann, Sebastian %A Haag, Carl %A Albrecht, Mario %A Feldbrügge, Michael %+ External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T A FYVE Zinc Finger Domain Protein Specifically Links mRNA Transport to Endosome Trafficking : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002A-5A2D-6 %R 10.7554/eLife.06041 %7 2015 %D 2015 %J eLife %Z sequence number: e06041 %I eLife Sciences Publications %C Cambridge
64. Schmidl C, Rendeiro AF, Sheffield NC, Bock C: ChIPmentation: Fast, Robust, Low-input ChIP-seq for Histones and Transcription Factors. Nature Methods 2015, 12.
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@article{Schmidl2015, TITLE = {{ChIPmentation}: {Fast}, Robust, Low-input {ChIP}-seq for Histones and Transcription Factors}, AUTHOR = {Schmidl, Christian and Rendeiro, Andr{\'e} F. and Sheffield, Nathan C. and Bock, Christoph}, LANGUAGE = {eng}, ISSN = {1548-7091}, DOI = {10.1038/nmeth.3542}, PUBLISHER = {Nature Pub. Group}, ADDRESS = {New York, NY}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, DATE = {2015}, JOURNAL = {Nature Methods}, VOLUME = {12}, NUMBER = {10}, PAGES = {963--965}, }
Endnote
%0 Journal Article %A Schmidl, Christian %A Rendeiro, André F. %A Sheffield, Nathan C. %A Bock, Christoph %+ External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T ChIPmentation: Fast, Robust, Low-input ChIP-seq for Histones and Transcription Factors : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0028-F6FD-C %R 10.1038/nmeth.3542 %2 PMC4589892 %7 2015 %D 2015 %J Nature Methods %O Nature methods %V 12 %N 10 %& 963 %P 963 - 965 %I Nature Pub. Group %C New York, NY %@ false
65. Schneider E, El Hajj N, Müller F, Navarro B: Epigenetic Dysregulation in the Prefrontal Cortex of Suicide Completers. Cytogenetics and Genome Research 2015, 146.
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@article{Muellerfab2015, TITLE = {Epigenetic Dysregulation in the Prefrontal Cortex of Suicide Completers}, AUTHOR = {Schneider, Ebahard and El Hajj, Nady and M{\"u}ller, Fabian and Navarro, Bianca}, LANGUAGE = {eng}, ISSN = {0301-0171}, DOI = {10.1159/000435778}, PUBLISHER = {Karger}, ADDRESS = {Basel}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, JOURNAL = {Cytogenetics and Genome Research}, VOLUME = {146}, NUMBER = {1}, PAGES = {19--27}, }
Endnote
%0 Journal Article %A Schneider, Ebahard %A El Hajj, Nady %A Müller, Fabian %A Navarro, Bianca %+ External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T Epigenetic Dysregulation in the Prefrontal Cortex of Suicide Completers : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0028-E0EF-0 %R 10.1159/000435778 %7 2015-09 %D 2015 %J Cytogenetics and Genome Research %O Cytogenet Genome Res. %V 146 %N 1 %& 19 %P 19 - 27 %I Karger %C Basel %@ false
66. Sierra S, Dybowski JN, Pironti A, Heider D, Güney L, Thielen A, Reuter S, Esser S, Fätkenheuer G, Lengauer T, Hoffmann D, Pfister H, Jensen B, Kaiser R: Parameters Influencing Baseline HIV-1 Genotypic Tropism Testing Related to Clinical Outcome in Patients on Maraviroc. PLoS ONE 2015, 10.
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@article{SierraPLoSONE2015, TITLE = {Parameters Influencing Baseline {HIV}-1 Genotypic Tropism Testing Related to Clinical Outcome in Patients on Maraviroc}, AUTHOR = {Sierra, Saleta and Dybowski, J. Nikolai and Pironti, Alejandro and Heider, Dominik and G{\"u}ney, Lisa and Thielen, Alexander and Reuter, Stefan and Esser, Stefan and F{\"a}tkenheuer, Gerd and Lengauer, Thomas and Hoffmann, Daniel and Pfister, Herbert and Jensen, Bj{\"o}rn and Kaiser, Rolf}, LANGUAGE = {eng}, ISSN = {1932-6203}, URL = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4430318&tool=pmcentrez&rendertype=abstract}, DOI = {10.1371/journal.pone.0125502}, PUBLISHER = {Public Library of Science}, ADDRESS = {San Francisco, CA}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, JOURNAL = {PLoS ONE}, VOLUME = {10}, NUMBER = {5}, EID = {e0125502}, }
Endnote
%0 Journal Article %A Sierra, Saleta %A Dybowski, J. Nikolai %A Pironti, Alejandro %A Heider, Dominik %A Güney, Lisa %A Thielen, Alexander %A Reuter, Stefan %A Esser, Stefan %A Fätkenheuer, Gerd %A Lengauer, Thomas %A Hoffmann, Daniel %A Pfister, Herbert %A Jensen, Björn %A Kaiser, Rolf %A contributor: Ceccherini-Silberstein, Francesca %+ External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations %T Parameters Influencing Baseline HIV-1 Genotypic Tropism Testing Related to Clinical Outcome in Patients on Maraviroc : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0027-7AC3-3 %F OTHER: accessionPMC4430318 %F OTHER: pmcidPMC4430318 %F OTHER: pmc-uid4430318 %R 10.1371/journal.pone.0125502 %F OTHER: publisher-idPONE-D-14-44999 %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4430318&tool=pmcentrez&rendertype=abstract %7 2015-05-13 %D 2015 %8 13.05.2015 %J PLoS ONE %V 10 %N 5 %Z sequence number: e0125502 %I Public Library of Science %C San Francisco, CA %@ false
67. Speicher NK, Pfeifer N: Integrating Different Data Types by Regularized Unsupervised Multiple Kernel Learning with Application to Cancer Subtype Discovery. Bioinformatics (Proc ISMB/ECCB 2015) 2015, 31.
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@article{SpeicherPfeifer2015, TITLE = {Integrating Different Data Types by Regularized Unsupervised Multiple Kernel Learning with Application to Cancer Subtype Discovery}, AUTHOR = {Speicher, Nora K. and Pfeifer, Nico}, LANGUAGE = {eng}, ISSN = {1367-4803}, DOI = {10.1093/bioinformatics/btv244}, PUBLISHER = {Oxford University Press}, ADDRESS = {Oxford}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, DATE = {2015}, JOURNAL = {Bioinformatics (Proc. ISMB/ECCB)}, VOLUME = {31}, NUMBER = {12}, PAGES = {i268--i275}, BOOKTITLE = {ISMB/ECCB 2015}, }
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%0 Journal Article %A Speicher, Nora K. %A Pfeifer, Nico %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Integrating Different Data Types by Regularized Unsupervised Multiple Kernel Learning with Application to Cancer Subtype Discovery : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0027-D2E9-9 %R 10.1093/bioinformatics/btv244 %7 2015 %D 2015 %J Bioinformatics %V 31 %N 12 %& i268 %P i268 - i275 %I Oxford University Press %C Oxford %@ false %B ISMB/ECCB 2015 %O ISMB/ECCB 2015
68. Stöckel D, Schmidt F, Trampert P, Lenhof H-P: CausalTrail: Testing Hypothesis Using Causal Bayesian Networks. Faculty of 1000 Research 2015, 4.
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@article{StoeckelF1000Research2015, TITLE = {CausalTrail: Testing Hypothesis Using Causal {Bayesian} Networks}, AUTHOR = {St{\"o}ckel, Daniel and Schmidt, Florian and Trampert, Patrick and Lenhof, Hans-Peter}, LANGUAGE = {eng}, DOI = {10.12688/f1000research.7647.1}, PUBLISHER = {BioMed Central}, ADDRESS = {London}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, JOURNAL = {Faculty of 1000 Research}, VOLUME = {4}, EID = {1520}, }
Endnote
%0 Journal Article %A Stöckel, Daniel %A Schmidt, Florian %A Trampert, Patrick %A Lenhof, Hans-Peter %+ External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations %T CausalTrail: Testing Hypothesis Using Causal Bayesian Networks : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0028-F706-0 %R 10.12688/f1000research.7647.1 %7 2015 %D 2015 %J Faculty of 1000 Research %O F1000Research %V 4 %Z sequence number: 1520 %I BioMed Central %C London
69. Susser S, Flinders M, Reesink HW, Zeuzem S, Lawyer G, Ghys A, Van Eygen V, Witek J, De Meyer S, Sarrazin C: Evolution of Hepatitis C Virus Quasispecies during Repeated Treatment with the NS3/4A Protease Inhibitor Telaprevir. Antimicrobial Agents and Chemotherapy 2015, 59.
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@article{Susser2015, TITLE = {Evolution of Hepatitis {C }Virus Quasispecies during Repeated Treatment with the {NS3}/{4A} Protease Inhibitor Telaprevir}, AUTHOR = {Susser, Simone and Flinders, Mathieu and Reesink, Henk W. and Zeuzem, Stefan and Lawyer, Glenn and Ghys, Anne and Van Eygen, Veerle and Witek, James and De Meyer, Sandra and Sarrazin, Christoph}, LANGUAGE = {eng}, ISSN = {0066-4804}, DOI = {10.1128/AAC.04911-14}, PUBLISHER = {American Society for Microbiology (ASM)}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, DATE = {2015}, JOURNAL = {Antimicrobial Agents and Chemotherapy}, VOLUME = {59}, NUMBER = {5}, PAGES = {2746--2755}, }
Endnote
%0 Journal Article %A Susser, Simone %A Flinders, Mathieu %A Reesink, Henk W. %A Zeuzem, Stefan %A Lawyer, Glenn %A Ghys, Anne %A Van Eygen, Veerle %A Witek, James %A De Meyer, Sandra %A Sarrazin, Christoph %+ External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations %T Evolution of Hepatitis C Virus Quasispecies during Repeated Treatment with the NS3/4A Protease Inhibitor Telaprevir : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0028-1345-A %R 10.1128/AAC.04911-14 %7 2015 %D 2015 %J Antimicrobial Agents and Chemotherapy %V 59 %N 5 %& 2746 %P 2746 - 2755 %I American Society for Microbiology (ASM) %@ false
70. Tomazou EM, Sheffield NC, Schmidl C, Schuster M, Schoenegger A, Datlinger P, Kubicek S, Bock C, Kovar H: Epigenome Mapping Reveals Distinct Modes of Gene Regulation and Widespread Enhancer Reprogramming by the Oncogenic Fusion Protein EWS-FLI1. Cell Reports 2015, 10.
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@article{BockCellReports2015a, TITLE = {Epigenome Mapping Reveals Distinct Modes of Gene Regulation and Widespread Enhancer Reprogramming by the Oncogenic Fusion Protein {EWS}-{FLI1}}, AUTHOR = {Tomazou, Eleni M. and Sheffield, Nathan C. and Schmidl, Christian and Schuster, Michael and Schoenegger, Andreas and Datlinger, Paul and Kubicek, Stefan and Bock, Christoph and Kovar, Heinrich}, DOI = {10.1016/j.celrep.2015.01.042}, PUBLISHER = {Cell Press}, ADDRESS = {Cambridge, MA}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, DATE = {2015}, JOURNAL = {Cell Reports}, VOLUME = {10}, NUMBER = {7}, PAGES = {1082--1095}, }
Endnote
%0 Journal Article %A Tomazou, Eleni M. %A Sheffield, Nathan C. %A Schmidl, Christian %A Schuster, Michael %A Schoenegger, Andreas %A Datlinger, Paul %A Kubicek, Stefan %A Bock, Christoph %A Kovar, Heinrich %+ external external external external external external external Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society external %T Epigenome Mapping Reveals Distinct Modes of Gene Regulation and Widespread Enhancer Reprogramming by the Oncogenic Fusion Protein EWS-FLI1 : %U http://hdl.handle.net/11858/00-001M-0000-0026-A0DB-4 %F ISI: 000349918700006 %R 10.1016/j.celrep.2015.01.042 %D 2015 %J Cell Reports %V 10 %N 7 %& 1082 %P 1082 - 1095 %I Cell Press %C Cambridge, MA
71. Wittler R, Marschall T, Schönhuth A, Mäkinen V: Repeat- and Error-aware Comparison of Deletions. Bioinformatics 2015, 31.
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@article{Marschall2015a, TITLE = {Repeat- and Error-aware Comparison of Deletions}, AUTHOR = {Wittler, Roland and Marschall, Tobias and Sch{\"o}nhuth, Alexander and M{\"a}kinen, Veli}, LANGUAGE = {eng}, ISSN = {1367-4803}, DOI = {10.1093/bioinformatics/btv304}, PUBLISHER = {Oxford University Press}, ADDRESS = {Oxford}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, DATE = {2015}, JOURNAL = {Bioinformatics}, VOLUME = {31}, NUMBER = {18}, PAGES = {2947--2954}, }
Endnote
%0 Journal Article %A Wittler, Roland %A Marschall, Tobias %A Schönhuth, Alexander %A Mäkinen, Veli %+ External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations %T Repeat- and Error-aware Comparison of Deletions : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0028-E11C-4 %R 10.1093/bioinformatics/btv304 %7 2015 %D 2015 %J Bioinformatics %V 31 %N 18 %& 2947 %P 2947 - 2954 %I Oxford University Press %C Oxford %@ false
72. Wiwie C, Baumbach J, Röttger R: Comparing the Performance of Biomedical Clustering Methods. Nature Methods 2015, 12.
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@article{WiwieComparing2015, TITLE = {Comparing the Performance of Biomedical Clustering Methods}, AUTHOR = {Wiwie, Christian and Baumbach, Jan and R{\"o}ttger, Richard}, LANGUAGE = {eng}, ISSN = {1548-7091}, DOI = {10.1038/nmeth.3583}, PUBLISHER = {Nature Pub. Group}, ADDRESS = {New York, NY}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, DATE = {2015}, JOURNAL = {Nature Methods}, VOLUME = {12}, PAGES = {1033--1038}, }
Endnote
%0 Journal Article %A Wiwie, Christian %A Baumbach, Jan %A Röttger, Richard %+ External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T Comparing the Performance of Biomedical Clustering Methods : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0029-226E-A %R 10.1038/nmeth.3583 %7 2015 %D 2015 %J Nature Methods %O Nature methods %V 12 %& 1033 %P 1033 - 1038 %I Nature Pub. Group %C New York, NY %@ false
73. Zeke A, Bastys T, Alexa A, Garai Á, Mészáros B, Kirsch K, Dosztányi Z, Kalinina OV, Reményi A: Systematic Discovery of Linear Binding Motifs Targeting an Ancient Protein Interaction Surface on MAP Kinases. Molecular Systems Biology 2015, 11.
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@article{BastysKalinina15, TITLE = {Systematic Discovery of Linear Binding Motifs Targeting an Ancient Protein Interaction Surface on {MAP} Kinases}, AUTHOR = {Zeke, Andr{\'a}s and Bastys, Tomas and Alexa, Anita and Garai, {\'A}gnes and M{\'e}sz{\'a}ros, B{\'a}lint and Kirsch, Kl{\'a}ra and Doszt{\'a}nyi, Zsuzsanna and Kalinina, Olga V. and Rem{\'e}nyi, Attila}, LANGUAGE = {eng}, ISSN = {1744-4292}, DOI = {10.15252/msb.20156269}, PUBLISHER = {EMBO Press}, ADDRESS = {Heidelberg}, YEAR = {2015}, MARGINALMARK = {$\bullet$}, JOURNAL = {Molecular Systems Biology}, VOLUME = {11}, NUMBER = {11}, PAGES = {1--29}, EID = {837}, }
Endnote
%0 Journal Article %A Zeke, András %A Bastys, Tomas %A Alexa, Anita %A Garai, Ágnes %A Mészáros, Bálint %A Kirsch, Klára %A Dosztányi, Zsuzsanna %A Kalinina, Olga V. %A Reményi, Attila %+ External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T Systematic Discovery of Linear Binding Motifs Targeting an Ancient Protein Interaction Surface on MAP Kinases : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0028-F563-E %R 10.15252/msb.20156269 %7 2015-11-04 %D 2015 %8 04.11.2015 %J Molecular Systems Biology %V 11 %N 11 %& 1 %P 1 - 29 %Z sequence number: 837 %I EMBO Press %C Heidelberg %@ false %U http://msb.embopress.org/content/11/11/837
2014
74. Ahmad M, Kalinina O, Lengauer T: Entropy Gain Due to Water Release Upon Ligand Binding. Journal of Cheminformatics 2014, 6.
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@article{DBLP:journals/jcheminf/AhmadKL14, TITLE = {Entropy Gain Due to Water Release Upon Ligand Binding}, AUTHOR = {Ahmad, Mazen and Kalinina, Olga and Lengauer, Thomas}, LANGUAGE = {eng}, ISSN = {1758-2946}, DOI = {10.1186/1758-2946-6-S1-P35}, PUBLISHER = {Springer}, ADDRESS = {Berlin}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, JOURNAL = {Journal of Cheminformatics}, VOLUME = {6}, NUMBER = {S-1}, EID = {P35}, }
Endnote
%0 Journal Article %A Ahmad, Mazen %A Kalinina, Olga %A Lengauer, Thomas %+ External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Entropy Gain Due to Water Release Upon Ligand Binding : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-6154-3 %R 10.1186/1758-2946-6-S1-P35 %7 2014 %D 2014 %J Journal of Cheminformatics %V 6 %N S-1 %Z sequence number: P35 %I Springer %C Berlin %@ false
75. Alcaraz N, Pauling J, Batra R, Barbosa E, Junge A, Christensen AGL, Azevedo V, Ditzel HJ, Baumbach J: KeyPathwayMiner 4.0: Condition-specific Pathway Analysis by Combining Multiple Omics Studies and Networks with Cytoscape. BMC Systems Biology 2014, 8.
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@article{AlcarazBMC2014, TITLE = {{KeyPathwayMiner} 4.0: Condition-specific Pathway Analysis by Combining Multiple Omics Studies and Networks with {Cytoscape}}, AUTHOR = {Alcaraz, Nicolas and Pauling, Josch and Batra, Richa and Barbosa, Eudes and Junge, Alexander and Christensen, Anne G. L. and Azevedo, Vasco and Ditzel, Henrik J. and Baumbach, Jan}, LANGUAGE = {eng}, ISSN = {1752-0509}, DOI = {10.1186/s12918-014-0099-x}, PUBLISHER = {BioMedCentral}, ADDRESS = {London}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, JOURNAL = {BMC Systems Biology}, VOLUME = {8}, EID = {99}, }
Endnote
%0 Journal Article %A Alcaraz, Nicolas %A Pauling, Josch %A Batra, Richa %A Barbosa, Eudes %A Junge, Alexander %A Christensen, Anne G. L. %A Azevedo, Vasco %A Ditzel, Henrik J. %A Baumbach, Jan %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T KeyPathwayMiner 4.0: Condition-specific Pathway Analysis by Combining Multiple Omics Studies and Networks with Cytoscape : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-6C98-D %F ISI: 000340909700001 %R 10.1186/s12918-014-0099-x %2 PMC4236746 %7 2014 %D 2014 %J BMC Systems Biology %V 8 %Z sequence number: 99 %I BioMedCentral %C London %@ false %U http://www.biomedcentral.com/1752-0509/8/99
76. Amabile G, Di Ruscio A, Müller F, Welner RS, Yang H, Ebralidze AK, Zhang H, Qi L, Martinelli G, Brummelkamp T, Le Beau MM, Figueroa ME, Bock C, Tenen DG: Cellular Reprogramming Erases Aberrant DNA Methylation and the Malignant Phenotype in Chronic Myeloid Leukemia. Blood 2014, 124.
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@article{AmabileBLOOD2014, TITLE = {Cellular Reprogramming Erases Aberrant {DNA} Methylation and the Malignant Phenotype in {Chronic Myeloid Leukemia}}, AUTHOR = {Amabile, Giovanni and Di Ruscio, Annalisa and M{\"u}ller, Fabian and Welner, Robert S. and Yang, Henry and Ebralidze, Alexander K. and Zhang, Hong and Qi, Lihua and Martinelli, Giovanni and Brummelkamp, Thijn and Le Beau, Michelle M. and Figueroa, Maria E. and Bock, Christoph and Tenen, Daniel G.}, LANGUAGE = {eng}, ISSN = {0006-4971}, PUBLISHER = {American Society of Hematology}, ADDRESS = {Washington, DC}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, JOURNAL = {Blood}, VOLUME = {124}, NUMBER = {21}, PAGES = {4524--4524}, }
Endnote
%0 Journal Article %A Amabile, Giovanni %A Di Ruscio, Annalisa %A Müller, Fabian %A Welner, Robert S. %A Yang, Henry %A Ebralidze, Alexander K. %A Zhang, Hong %A Qi, Lihua %A Martinelli, Giovanni %A Brummelkamp, Thijn %A Le Beau, Michelle M. %A Figueroa, Maria E. %A Bock, Christoph %A Tenen, Daniel G. %+ External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations %T Cellular Reprogramming Erases Aberrant DNA Methylation and the Malignant Phenotype in Chronic Myeloid Leukemia : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0025-ACB5-3 %F ISI: 000349243500052 %7 2014 %D 2014 %J Blood %O Blood %V 124 %N 21 %& 4524 %P 4524 - 4524 %I American Society of Hematology %C Washington, DC %@ false
77. Assenov Y: Identification and Prioritization of Genomic Loci with Disease-specific Methylation. Universität des Saarlandes; 2014.
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@phdthesis{AssenovPhD2014, TITLE = {Identification and Prioritization of Genomic Loci with Disease-specific Methylation}, AUTHOR = {Assenov, Yassen}, LANGUAGE = {eng}, URL = {urn:nbn:de:bsz:291-scidok-58865}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, }
Endnote
%0 Thesis %A Assenov, Yassen %Y Lengauer, Thomas %A referee: Bock, Christoph %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society International Max Planck Research School, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Identification and Prioritization of Genomic Loci with Disease-specific Methylation : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-E49E-D %U urn:nbn:de:bsz:291-scidok-58865 %I Universität des Saarlandes %C Saarbrücken %D 2014 %P IX, 142 p. %V phd %9 phd %U http://scidok.sulb.uni-saarland.de/doku/lic_ohne_pod.php?la=dehttp://scidok.sulb.uni-saarland.de/volltexte/2014/5886/
78. Assenov Y, Müller F, Lutsik P, Walter J, Lengauer T, Bock C: Comprehensive Analysis of DNA Methylation Data with RnBeads. Nature Methods 2014, 11.
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@article{Assenov:2014kqa, TITLE = {Comprehensive Analysis of {DNA} Methylation Data with {RnBeads}}, AUTHOR = {Assenov, Yassen and M{\"u}ller, Fabian and Lutsik, Pavlo and Walter, J{\"o}rn and Lengauer, Thomas and Bock, Christoph}, LANGUAGE = {eng}, DOI = {10.1038/nmeth.3115}, PUBLISHER = {Nature Publishing Group}, ADDRESS = {London}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, JOURNAL = {Nature Methods}, VOLUME = {11}, NUMBER = {11}, PAGES = {1138--1140}, }
Endnote
%0 Journal Article %A Assenov, Yassen %A Müller, Fabian %A Lutsik, Pavlo %A Walter, Jörn %A Lengauer, Thomas %A Bock, Christoph %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Comprehensive Analysis of DNA Methylation Data with RnBeads : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-5D25-A %2 PMC4216143 %R 10.1038/nmeth.3115 %7 2014 %D 2014 %J Nature Methods %V 11 %N 11 %& 1138 %P 1138 - 1140 %I Nature Publishing Group %C London %U http://www.ncbi.nlm.nih.gov/pubmed/25262207
79. Barbosa E, Röttger R, Hauschild A-C, Azevedo V, Baumbach J: On the Limits of Computational Functional Genomics for Bacterial Lifestyle Prediction. Briefings in Functional Genomics 2014, 13.
Abstract
We review the level of genomic specificity regarding actinobacterial pathogenicity. As they occupy various niches in diverse habitats, one may assume the existence of lifestyle-specific genomic features. We include 240 actinobacteria classified into four pathogenicity classes: human pathogens (HPs), broad-spectrum pathogens (BPs), opportunistic pathogens (OPs) and non-pathogenic (NP). We hypothesize: (H1) Pathogens (HPs and BPs) possess specific pathogenicity signature genes. (H2) The same holds for OPs. (H3) Broad-spectrum and exclusively HPs cannot be distinguished from each other because of an observation bias, i.e. many HPs might yet be unclassified BPs. (H4) There is no intrinsic genomic characteristic of OPs compared with pathogens, as small mutations are likely to play a more dominant role to survive the immune system. To study these hypotheses, we implemented a bioinformatics pipeline that combines evolutionary sequence analysis with statistical learning methods (Random Forest with feature selection, model tuning and robustness analysis). Essentially, we present orthologous gene sets that computationally distinguish pathogens from NPs (H1). We further show a clear limit in differentiating OPs from both NPs (H2) and pathogens (H4). HPs may also not be distinguished from bacteria annotated as BPs based only on a small set of orthologous genes (H3), as many HPs might as well target a broad range of mammals but have not been annotated accordingly. In conclusion, we illustrate that even in the post-genome era and despite next-generation sequencing technology, our ability to efficiently deduce real-world conclusions, such as pathogenicity classification, remains quite limited.
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@article{Barbosa2014, TITLE = {On the Limits of Computational Functional Genomics for Bacterial Lifestyle Prediction}, AUTHOR = {Barbosa, Eudes and R{\"o}ttger, Richard and Hauschild, Anne-Christin and Azevedo, Vasco and Baumbach, Jan}, LANGUAGE = {eng}, DOI = {10.1093/bfgp/elu014}, PUBLISHER = {Oxford University Press}, ADDRESS = {Oxford}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014-09-01}, ABSTRACT = {We review the level of genomic specificity regarding actinobacterial pathogenicity. As they occupy various niches in diverse habitats, one may assume the existence of lifestyle-specific genomic features. We include 240 actinobacteria classified into four pathogenicity classes: human pathogens (HPs), broad-spectrum pathogens (BPs), opportunistic pathogens (OPs) and non-pathogenic (NP). We hypothesize: (H1) Pathogens (HPs and BPs) possess specific pathogenicity signature genes. (H2) The same holds for OPs. (H3) Broad-spectrum and exclusively HPs cannot be distinguished from each other because of an observation bias, i.e. many HPs might yet be unclassified BPs. (H4) There is no intrinsic genomic characteristic of OPs compared with pathogens, as small mutations are likely to play a more dominant role to survive the immune system. To study these hypotheses, we implemented a bioinformatics pipeline that combines evolutionary sequence analysis with statistical learning methods (Random Forest with feature selection, model tuning and robustness analysis). Essentially, we present orthologous gene sets that computationally distinguish pathogens from NPs (H1). We further show a clear limit in differentiating OPs from both NPs (H2) and pathogens (H4). HPs may also not be distinguished from bacteria annotated as BPs based only on a small set of orthologous genes (H3), as many HPs might as well target a broad range of mammals but have not been annotated accordingly. In conclusion, we illustrate that even in the post-genome era and despite next-generation sequencing technology, our ability to efficiently deduce real-world conclusions, such as pathogenicity classification, remains quite limited.}, JOURNAL = {Briefings in Functional Genomics}, VOLUME = {13}, NUMBER = {5}, PAGES = {398--408}, }
Endnote
%0 Journal Article %A Barbosa, Eudes %A Röttger, Richard %A Hauschild, Anne-Christin %A Azevedo, Vasco %A Baumbach, Jan %+ External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T On the Limits of Computational Functional Genomics for Bacterial Lifestyle Prediction : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-551D-2 %R 10.1093/bfgp/elu014 %7 2014-05-22 %D 2014 %8 01.09.2014 %X We review the level of genomic specificity regarding actinobacterial pathogenicity. As they occupy various niches in diverse habitats, one may assume the existence of lifestyle-specific genomic features. We include 240 actinobacteria classified into four pathogenicity classes: human pathogens (HPs), broad-spectrum pathogens (BPs), opportunistic pathogens (OPs) and non-pathogenic (NP). We hypothesize: (H1) Pathogens (HPs and BPs) possess specific pathogenicity signature genes. (H2) The same holds for OPs. (H3) Broad-spectrum and exclusively HPs cannot be distinguished from each other because of an observation bias, i.e. many HPs might yet be unclassified BPs. (H4) There is no intrinsic genomic characteristic of OPs compared with pathogens, as small mutations are likely to play a more dominant role to survive the immune system. To study these hypotheses, we implemented a bioinformatics pipeline that combines evolutionary sequence analysis with statistical learning methods (Random Forest with feature selection, model tuning and robustness analysis). Essentially, we present orthologous gene sets that computationally distinguish pathogens from NPs (H1). We further show a clear limit in differentiating OPs from both NPs (H2) and pathogens (H4). HPs may also not be distinguished from bacteria annotated as BPs based only on a small set of orthologous genes (H3), as many HPs might as well target a broad range of mammals but have not been annotated accordingly. In conclusion, we illustrate that even in the post-genome era and despite next-generation sequencing technology, our ability to efficiently deduce real-world conclusions, such as pathogenicity classification, remains quite limited. %J Briefings in Functional Genomics %V 13 %N 5 %& 398 %P 398 - 408 %I Oxford University Press %C Oxford %U http://bfgp.oxfordjournals.org/content/13/5/398.abstract
80. Bastys T, Doncheva NT, Walter H, Kaiser R, Albrecht M, Kalinina OV: Molecular Mechanisms of HIV-1 Protease Resistance and Resensitization towards Lopinavir and Saquinavir upon L76V Mutation. Antiviral Therapy 2014(Suppl. 1).
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@inproceedings{Bastys2014x, TITLE = {Molecular Mechanisms of {HIV}-1 Protease Resistance and Resensitization towards Lopinavir and Saquinavir upon {L76V} Mutation}, AUTHOR = {Bastys, Tomas and Doncheva, Nadezhda Tsankova and Walter, Hauke and Kaiser, R. and Albrecht, Mario and Kalinina, Olga V.}, LANGUAGE = {eng}, ISSN = {1359-6535}, PUBLISHER = {International Medical Press}, PUBLISHER = {International Medical Press}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, BOOKTITLE = {Abstracts presented at the International Workshop on Antiviral Drug Resistance: Meeting the Global Challenge}, JOURNAL = {Antiviral Therapy}, VOLUME = {19}, ISSUE = {Suppl. 1}, EID = {A154}, ADDRESS = {Berlin, Germany}, }
Endnote
%0 Generic %A Bastys, Tomas %A Doncheva, Nadezhda Tsankova %A Walter, Hauke %A Kaiser, R. %A Albrecht, Mario %A Kalinina, Olga V. %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Molecular Mechanisms of HIV-1 Protease Resistance and Resensitization towards Lopinavir and Saquinavir upon L76V Mutation : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0027-9CE8-7 %D 2014 %Z name of event: International Workshop on Antiviral Drug Resistance: Meeting the Global Challenge %Z date of event: 2014-06-03 - 2014-06-07 %Z place of event: Berlin, Germany %B Abstracts presented at the International Workshop on Antiviral Drug Resistance: Meeting the Global Challenge %J Antiviral Therapy %V 19 %N Suppl. 1 %Z sequence number: A154 %@ false
81. Becker D: BiQ Analyzer HiMod - an Interactive Software Tool for High-throughput Locus-specific Analysis of 5-Methylcyclosine and its Oxidized Derivatives. Universität des Saarlandes; 2014.
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@mastersthesis{Becker2014, TITLE = {{BiQ} Analyzer {HiMod} -- an Interactive Software Tool for High-throughput Locus-specific Analysis of 5-Methylcyclosine and its Oxidized Derivatives}, AUTHOR = {Becker, Daniel}, LANGUAGE = {eng}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, }
Endnote
%0 Thesis %A Becker, Daniel %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T BiQ Analyzer HiMod - an Interactive Software Tool for High-throughput Locus-specific Analysis of 5-Methylcyclosine and its Oxidized Derivatives : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-C278-D %I Universität des Saarlandes %C Saarbrücken %D 2014 %V master %9 master
82. Becker D, Lutsik P, Ebert P, Bock C, Lengauer T, Walter J: BiQ Analyzer HiMod: An Interactive Software Tool for High-throughput Locus-specific Analysis of 5-Methylcytosine and its Oxidized Derivatives. Nucleic Acids Research 2014, 42.
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@article{BeckerBiQ2014, TITLE = {{BiQ} Analyzer {HiMod}: An Interactive Software Tool for High-throughput Locus-specific Analysis of 5-Methylcytosine and its Oxidized Derivatives}, AUTHOR = {Becker, Daniel and Lutsik, Pavlo and Ebert, Peter and Bock, Christoph and Lengauer, Thomas and Walter, J{\"o}rn}, LANGUAGE = {eng}, ISSN = {0305-1048; 1362-4962}, URL = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4086109&tool=pmcentrez&rendertype=abstract}, DOI = {10.1093/nar/gku457}, PUBLISHER = {Oxford University Press}, ADDRESS = {Oxford, UK}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014-07-01}, JOURNAL = {Nucleic Acids Research}, VOLUME = {42}, NUMBER = {W1}, PAGES = {W501--W507}, }
Endnote
%0 Journal Article %A Becker, Daniel %A Lutsik, Pavlo %A Ebert, Peter %A Bock, Christoph %A Lengauer, Thomas %A Walter, Jörn %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T BiQ Analyzer HiMod: An Interactive Software Tool for High-throughput Locus-specific Analysis of 5-Methylcytosine and its Oxidized Derivatives : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-6BE8-1 %F OTHER: accessionPMC4086109 %F OTHER: pmcidPMC4086109 %F OTHER: pmc-uid4086109 %R 10.1093/nar/gku457 %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4086109&tool=pmcentrez&rendertype=abstract %7 2014-05-29 %D 2014 %8 01.07.2014 %J Nucleic Acids Research %V 42 %N W1 %& W501 %P W501 - W507 %I Oxford University Press %C Oxford, UK %@ false
83. Beggel B: Determining and Utilizing the Quasispecies of the Hepatitis B Virus in Clinical Applications. Universität des Saarlandes; 2014.
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@phdthesis{Beggeltheses2014, TITLE = {Determining and Utilizing the Quasispecies of the Hepatitis {B} Virus in Clinical Applications}, AUTHOR = {Beggel, Bastian}, LANGUAGE = {eng}, URL = {urn:nbn:de:bsz:291-scidok-58317}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, }
Endnote
%0 Thesis %A Beggel, Bastian %Y Lengauer, Thomas %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society International Max Planck Research School, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Determining and Utilizing the Quasispecies of the Hepatitis B Virus in Clinical Applications : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-5DFB-A %U urn:nbn:de:bsz:291-scidok-58317 %I Universität des Saarlandes %C Saarbrücken %D 2014 %P 138 p. %V phd %9 phd %U http://scidok.sulb.uni-saarland.de/volltexte/2014/5831/http://scidok.sulb.uni-saarland.de/doku/lic_ohne_pod.php?la=de
84. Blankenburg H: Computational Methods for Integrating and Analyzing Human Systems Biology Data. Universität des Saarlandes; 2014.
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@phdthesis{Blankenburg2014, TITLE = {Computational Methods for Integrating and Analyzing Human Systems Biology Data}, AUTHOR = {Blankenburg, Hagen}, LANGUAGE = {eng}, URL = {urn:nbn:de:bsz:291-scidok-59329}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, }
Endnote
%0 Thesis %A Blankenburg, Hagen %Y Albrecht, Mario %A referee: Helms, Volkhard %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society International Max Planck Research School, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T Computational Methods for Integrating and Analyzing Human Systems Biology Data : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-9671-3 %U urn:nbn:de:bsz:291-scidok-59329 %I Universität des Saarlandes %C Saarbrücken %D 2014 %P 181 p. %V phd %9 phd %U http://scidok.sulb.uni-saarland.de/doku/lic_ohne_pod.php?la=dehttp://scidok.sulb.uni-saarland.de/volltexte/2014/5932/
85. Bock C: Synergy and Competition between Cancer Genome Sequencing and Epigenome Mapping Projects. Genome Medicine 2014, 6.
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@article{BockSynergy2014, TITLE = {Synergy and Competition between Cancer Genome Sequencing and Epigenome Mapping Projects}, AUTHOR = {Bock, Christoph}, LANGUAGE = {eng}, ISSN = {1756-994X}, DOI = {10.1186/gm557}, PUBLISHER = {BioMed Central}, ADDRESS = {London}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, JOURNAL = {Genome Medicine}, VOLUME = {6}, NUMBER = {5}, EID = {41}, }
Endnote
%0 Journal Article %A Bock, Christoph %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Synergy and Competition between Cancer Genome Sequencing and Epigenome Mapping Projects : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-6BF1-D %R 10.1186/gm557 %2 PMC4062064 %7 2014 %D 2014 %J Genome Medicine %V 6 %N 5 %Z sequence number: 41 %I BioMed Central %C London %@ false %U http://genomemedicine.com/content/6/5/41
86. Deplus R, Blanchon L, Rajavelu A, Boukaba A, Defrance M, Luciani J, Rothe F, Dedeurwaerder S, Denis H, Brinkman AB, Simmer F, Müller F, Bertin B, Berdasco M, Putmans P, Calonne E, Litchfield DW, de Launoit Y, Jurkowski TP, Stunnenberg HG, Bock C, Sotiriou C, Fraga MF, Esteller M, Jeltsch A, Fuks F: Regulation of DNA Methylation Patterns by CK2-mediated Phosphorylation of Dnmt3a. Cell Reports 2014, 8.
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@article{escidoc:2072324, TITLE = {Regulation of {DNA} Methylation Patterns by {CK2}-mediated Phosphorylation of {Dnmt3a}}, AUTHOR = {Deplus, Rachel and Blanchon, Lo{\"i}c and Rajavelu, Arumugam and Boukaba, Abdelhalim and Defrance, Matthieu and Luciani, Judith and Rothe, Fran{\c c}oise and Dedeurwaerder, Sarah and Denis, H{\'e}l{\`e}ne and Brinkman, Arie B. and Simmer, Femke and M{\"u}ller, Fabian and Bertin, Benjamin and Berdasco, Maria and Putmans, Pascale and Calonne, Emilie and Litchfield, David W. and de Launoit, Yvan and Jurkowski, Tomasz P. and Stunnenberg, Hendrik G. and Bock, Christoph and Sotiriou, Christos and Fraga, Mario F. and Esteller, Manel and Jeltsch, Albert and Fuks, Fran{\c c}ois}, LANGUAGE = {eng}, DOI = {10.1016/j.celrep.2014.06.048}, PUBLISHER = {Elsevier}, ADDRESS = {Amsterdam}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, JOURNAL = {Cell Reports}, VOLUME = {8}, NUMBER = {3}, PAGES = {743--753}, }
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%0 Journal Article %A Deplus, Rachel %A Blanchon, Loïc %A Rajavelu, Arumugam %A Boukaba, Abdelhalim %A Defrance, Matthieu %A Luciani, Judith %A Rothe, Françoise %A Dedeurwaerder, Sarah %A Denis, Hélène %A Brinkman, Arie B. %A Simmer, Femke %A Müller, Fabian %A Bertin, Benjamin %A Berdasco, Maria %A Putmans, Pascale %A Calonne, Emilie %A Litchfield, David W. %A de Launoit, Yvan %A Jurkowski, Tomasz P. %A Stunnenberg, Hendrik G. %A Bock, Christoph %A Sotiriou, Christos %A Fraga, Mario F. %A Esteller, Manel %A Jeltsch, Albert %A Fuks, François %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations %T Regulation of DNA Methylation Patterns by CK2-mediated Phosphorylation of Dnmt3a : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-6BE1-F %F ISI: 000341572200012 %R 10.1016/j.celrep.2014.06.048 %7 2014 %D 2014 %J Cell Reports %V 8 %N 3 %& 743 %P 743 - 753 %I Elsevier %C Amsterdam %U http://www.sciencedirect.com/science/article/pii/S2211124714005324
87. Dietzen M: Modeling Protein Interactions in Protein Binding Sites and Oligomeric Protein Complexes. Universität des Saarlandes; 2014.
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@phdthesis{DietzenPhD2014, TITLE = {Modeling Protein Interactions in Protein Binding Sites and Oligomeric Protein Complexes}, AUTHOR = {Dietzen, Matthias}, LANGUAGE = {eng}, URL = {urn:nbn:de:bsz:291-scidok-59402}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, }
Endnote
%0 Thesis %A Dietzen, Matthias %Y Lengauer, Thomas %A referee: Hildebrandt, Andreas %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society International Max Planck Research School, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T Modeling Protein Interactions in Protein Binding Sites and Oligomeric Protein Complexes : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-E4A2-1 %U urn:nbn:de:bsz:291-scidok-59402 %I Universität des Saarlandes %C Saarbrücken %D 2014 %P XVIII, 259 p. %V phd %9 phd %U http://scidok.sulb.uni-saarland.de/doku/lic_ohne_pod.php?la=dehttp://scidok.sulb.uni-saarland.de/volltexte/2014/5940/
88. Dietzen M, Zotenko E, Hildebrandt A, Lengauer T: Correction to On the Applicability of Elastic Network Normal Modes in Small-molecule Docking. Journal of Chemical Information and Modeling 2014, 54.
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@article{doi:10.1021/ci5006788, TITLE = {Correction to {O}n the Applicability of Elastic Network Normal Modes in Small-molecule Docking}, AUTHOR = {Dietzen, Matthias and Zotenko, Elena and Hildebrandt, Andreas and Lengauer, Thomas}, LANGUAGE = {eng}, ISSN = {1549-9596}, DOI = {10.1021/ci5006788}, PUBLISHER = {American Chemical Society}, ADDRESS = {Washington, DC}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, JOURNAL = {Journal of Chemical Information and Modeling}, VOLUME = {54}, NUMBER = {12}, PAGES = {3453--3453}, }
Endnote
%0 Journal Article %A Dietzen, Matthias %A Zotenko, Elena %A Hildebrandt, Andreas %A Lengauer, Thomas %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Correction to On the Applicability of Elastic Network Normal Modes in Small-molecule Docking : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-925B-A %R 10.1021/ci5006788 %7 2014 %D 2014 %J Journal of Chemical Information and Modeling %V 54 %N 12 %& 3453 %P 3453 - 3453 %I American Chemical Society %C Washington, DC %@ false
89. Dirks M, Pfeifer N, Schulter E, Esser S, Fatkenheuer G, Jenssen B, Kaiser R, Verheyen J: Insertions and Deletions in p6-gag Correlate with the Predicted Cellular Tropism of HIV-1 V3 Sequences. Antiviral Therapy 2014(Suppl. 1).
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@inproceedings{Dirks2014x, TITLE = {Insertions and Deletions in p6-gag Correlate with the Predicted Cellular Tropism of {HIV}-1 V3 Sequences}, AUTHOR = {Dirks, M. and Pfeifer, Nico and Schulter, E. and Esser, S. and Fatkenheuer, G. and Jenssen, B. and Kaiser, R. and Verheyen, J.}, LANGUAGE = {eng}, ISSN = {1359-6535}, PUBLISHER = {International Medical Press}, PUBLISHER = {International Medical Press}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, BOOKTITLE = {Abstracts presented at the International Workshop on Antiviral Drug Resistance: Meeting the Global Challenge}, JOURNAL = {Antiviral Therapy}, VOLUME = {19}, ISSUE = {Suppl. 1}, EID = {A116}, ADDRESS = {Berlin, Germany}, }
Endnote
%0 Generic %A Dirks, M. %A Pfeifer, Nico %A Schulter, E. %A Esser, S. %A Fatkenheuer, G. %A Jenssen, B. %A Kaiser, R. %A Verheyen, J. %+ External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations %T Insertions and Deletions in p6-gag Correlate with the Predicted Cellular Tropism of HIV-1 V3 Sequences : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0027-9CF8-3 %D 2014 %Z name of event: International Workshop on Antiviral Drug Resistance: Meeting the Global Challenge %Z date of event: 2014-06-03 - 2014-06-07 %Z place of event: Berlin, Germany %B Abstracts presented at the International Workshop on Antiviral Drug Resistance: Meeting the Global Challenge %J Antiviral Therapy %V 19 %N Suppl. 1 %Z sequence number: A116 %@ false
90. Doncheva NT, Klein K, Morris JH, Wybrow M, Domingues FS, Albrecht M: Integrative Visual Analysis of Protein Sequence Mutations. BMC Proceedings (Proc BioVis 2013) 2014, 8(Suppl 2).
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@article{doncheva14a, TITLE = {Integrative Visual Analysis of Protein Sequence Mutations}, AUTHOR = {Doncheva, Nadezhda Tsankova and Klein, Karsten and Morris, John H. and Wybrow, Michael and Domingues, Francisco S. and Albrecht, Mario}, LANGUAGE = {eng}, ISSN = {1753-6561}, DOI = {10.1186/1753-6561-8-S2-S2}, PUBLISHER = {BioMed Central}, ADDRESS = {London}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, JOURNAL = {BMC Proceedings (Proc. BioVis)}, VOLUME = {8}, NUMBER = {Suppl 2}, EID = {S2}, BOOKTITLE = {Proceedings of the 3rd Annual Symposium on Biological Data Visualization: Data Analysis and Redesign Contests (BioVis 2013)}, }
Endnote
%0 Journal Article %A Doncheva, Nadezhda Tsankova %A Klein, Karsten %A Morris, John H. %A Wybrow, Michael %A Domingues, Francisco S. %A Albrecht, Mario %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations %T Integrative Visual Analysis of Protein Sequence Mutations : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-5D70-D %R 10.1186/1753-6561-8-S2-S2 %7 2014-08-28 %D 2014 %8 28.08.2014 %J BMC Proceedings %V 8 %N Suppl 2 %Z sequence number: S2 %I BioMed Central %C London %@ false %B Proceedings of the 3rd Annual Symposium on Biological Data Visualization: Data Analysis and Redesign Contests %O 3rd IEEE Symposium on Biological Data Visualization ; Atlanta, GA, USA ; 13-14 October 2013 BioVis 2013 %U http://www.biomedcentral.com/1753-6561/8/S2/S2
91. Döring M: Identification and Analysis of Methylation Call Differences Between Bisulphite Microarray and Bisulphite Sequencing Data With Statistical Learning Techniques. Universität des Saarlandes; 2014.
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@mastersthesis{Doering2014, TITLE = {Identification and Analysis of Methylation Call Differences Between Bisulphite Microarray and Bisulphite Sequencing Data With Statistical Learning Techniques}, AUTHOR = {D{\"o}ring, Matthias}, LANGUAGE = {eng}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, }
Endnote
%0 Thesis %A Döring, Matthias %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Identification and Analysis of Methylation Call Differences Between Bisulphite Microarray and Bisulphite Sequencing Data With Statistical Learning Techniques : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-C276-2 %I Universität des Saarlandes %C Saarbrücken %D 2014 %V master %9 master
92. Eckel SP, Baumbach J, Hauschild A-C: On the Importance of Statistics in Breath Analysis -- Hope or Curse? Journal of Breath Research 2014, 8.
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@article{Eckel2014, TITLE = {On the Importance of Statistics in Breath Analysis -- Hope or Curse?}, AUTHOR = {Eckel, Sandrah P. and Baumbach, Jan and Hauschild, Anne-Christin}, LANGUAGE = {eng}, ISSN = {1752-7155}, DOI = {10.1088/1752-7155/8/1/012001}, PUBLISHER = {IOP Publ.}, ADDRESS = {Bristol, UK}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, JOURNAL = {Journal of Breath Research}, VOLUME = {8}, NUMBER = {1}, PAGES = {1--4}, EID = {012001}, }
Endnote
%0 Journal Article %A Eckel, Sandrah P. %A Baumbach, Jan %A Hauschild, Anne-Christin %+ External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T On the Importance of Statistics in Breath Analysis -- Hope or Curse? : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-3DF7-0 %F ISI: 000332654800001 %R 10.1088/1752-7155/8/1/012001 %2 PMC4014528 %7 2014-02-24 %D 2014 %8 24.02.2014 %J Journal of Breath Research %V 8 %N 1 %& 1 %P 1 - 4 %Z sequence number: 012001 %I IOP Publ. %C Bristol, UK %@ false
93. Feldmann A: Predicting HIV-1 Susceptibility to Broadly Neutralizing Antibodies. Universität des Saarlandes; 2014.
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@mastersthesis{Feldmann2014, TITLE = {Predicting {HIV}-1 Susceptibility to Broadly Neutralizing Antibodies}, AUTHOR = {Feldmann, Anna}, LANGUAGE = {eng}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, }
Endnote
%0 Thesis %A Feldmann, Anna %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Predicting HIV-1 Susceptibility to Broadly Neutralizing Antibodies : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-C27F-0 %I Universität des Saarlandes %C Saarbrücken %D 2014 %V master %9 master
94. Feuerbach L: Evolutionary Epigenomics - Identifying Functional Genome Elements by Epigenetic Footprints in the DNA. Universität des Saarlandes; 2014.
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@phdthesis{Feuerbach2014, TITLE = {Evolutionary Epigenomics -- Identifying Functional Genome Elements by Epigenetic Footprints in the {DNA}}, AUTHOR = {Feuerbach, Lars}, LANGUAGE = {eng}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, }
Endnote
%0 Thesis %A Feuerbach, Lars %Y Lengauer, Thomas %A referee: Jotun, Hein %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society International Max Planck Research School, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T Evolutionary Epigenomics - Identifying Functional Genome Elements by Epigenetic Footprints in the DNA : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-9676-A %I Universität des Saarlandes %C Saarbrücken %D 2014 %P 205 p. %V phd %9 phd %U http://scidok.sulb.uni-saarland.de/doku/lic_ohne_pod.php?la=dehttp://scidok.sulb.uni-saarland.de/volltexte/2014/5888/
95. Grund S, Gkioule C, Termos T, Pfeifer N, Kobbe G, Verheyen J, Adams O: Primarily Oseltamivir Resistant Influenza A (H1N1pdm09) Virus Evolving into a Multi-drug Resistant Virus Carrying H275Y and I223R Neuraminidase Substitutions. Antiviral Therapy 2014, 20.
Abstract
Antiviral susceptibility testing and reporting of viruses carrying amino acid substitutions conferring antiviral drug resistance is essential to assess the spread and clinical impact of these viruses. Here we report on a patient who was infected with a primarily oseltamivir resistant influenza A (H1N1pdm09) virus following allogeneic stem cell transplantation and rituximab treatment. Under prolonged virus replication and zanamivir therapy the neuraminidase amino acid substitutions H275Y and I223R were detected conferring high-level resistance to oseltamivir and cross-resistance to zanamivir. The emergence of these amino acid changes has been reported rarely worldwide and has been associated with fatal clinical outcomes. The patient survived the influenza infection after 170 days of follow-up.
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@article{Grund2014, TITLE = {Primarily Oseltamivir Resistant Influenza {A} ({H1N1pdm09}) Virus Evolving into a Multi-drug Resistant Virus Carrying {H275Y} and {I223R} Neuraminidase Substitutions}, AUTHOR = {Grund, Sebastian and Gkioule, Charikleia and Termos, Tahani and Pfeifer, Nico and Kobbe, Guido and Verheyen, Jens and Adams, Ortwin}, LANGUAGE = {eng}, ISSN = {1359-6535}, DOI = {10.3851/IMP2811}, PUBLISHER = {International Medical Press}, ADDRESS = {London}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, ABSTRACT = {Antiviral susceptibility testing and reporting of viruses carrying amino acid substitutions conferring antiviral drug resistance is essential to assess the spread and clinical impact of these viruses. Here we report on a patient who was infected with a primarily oseltamivir resistant influenza A (H1N1pdm09) virus following allogeneic stem cell transplantation and rituximab treatment. Under prolonged virus replication and zanamivir therapy the neuraminidase amino acid substitutions H275Y and I223R were detected conferring high-level resistance to oseltamivir and cross-resistance to zanamivir. The emergence of these amino acid changes has been reported rarely worldwide and has been associated with fatal clinical outcomes. The patient survived the influenza infection after 170 days of follow-up.}, JOURNAL = {Antiviral Therapy}, VOLUME = {20}, NUMBER = {1}, PAGES = {97--100}, }
Endnote
%0 Journal Article %A Grund, Sebastian %A Gkioule, Charikleia %A Termos, Tahani %A Pfeifer, Nico %A Kobbe, Guido %A Verheyen, Jens %A Adams, Ortwin %+ External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations %T Primarily Oseltamivir Resistant Influenza A (H1N1pdm09) Virus Evolving into a Multi-drug Resistant Virus Carrying H275Y and I223R Neuraminidase Substitutions : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-901B-E %R 10.3851/IMP2811 %7 2014 %D 2014 %X Antiviral susceptibility testing and reporting of viruses carrying amino acid substitutions conferring antiviral drug resistance is essential to assess the spread and clinical impact of these viruses. Here we report on a patient who was infected with a primarily oseltamivir resistant influenza A (H1N1pdm09) virus following allogeneic stem cell transplantation and rituximab treatment. Under prolonged virus replication and zanamivir therapy the neuraminidase amino acid substitutions H275Y and I223R were detected conferring high-level resistance to oseltamivir and cross-resistance to zanamivir. The emergence of these amino acid changes has been reported rarely worldwide and has been associated with fatal clinical outcomes. The patient survived the influenza infection after 170 days of follow-up. %J Antiviral Therapy %V 20 %N 1 %& 97 %P 97 - 100 %I International Medical Press %C London %@ false %U http://www.ncbi.nlm.nih.gov/pubmed/24941247
96. Halachev K: Exploratory Visualizations and Statistical Analysis of Large, Heterogeneous Epigenetic Datasets. Universität des Saarlandes; 2014.
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@phdthesis{Halachev2014, TITLE = {Exploratory Visualizations and Statistical Analysis of Large, Heterogeneous Epigenetic Datasets}, AUTHOR = {Halachev, Konstantin}, LANGUAGE = {eng}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, }
Endnote
%0 Thesis %A Halachev, Konstantin %Y Lengauer, Thomas %A referee: Bock, Christoph %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society International Max Planck Research School, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Exploratory Visualizations and Statistical Analysis of Large, Heterogeneous Epigenetic Datasets : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-96A8-9 %I Universität des Saarlandes %C Saarbrücken %D 2014 %P 163 p. %V phd %9 phd %U http://scidok.sulb.uni-saarland.de/doku/lic_ohne_pod.php?la=dehttp://scidok.sulb.uni-saarland.de/volltexte/2014/5911/
97. Hauschild A-C, Baumbach JI, Baumbach J: Novel Developments In Computational Clinical Breath Analysis and Biomarker Detection. In ECCB’14 Highlight Papers Abstracts; 2014.
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@inproceedings{HauschildECCB2014, TITLE = {Novel Developments In Computational Clinical Breath Analysis and Biomarker Detection}, AUTHOR = {Hauschild, Anne-Christin and Baumbach, J{\"o}rg Ingo and Baumbach, Jan}, LANGUAGE = {eng}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, BOOKTITLE = {ECCB'14 Highlight Papers Abstracts}, EID = {HP09}, ADDRESS = {Strasbourg, France}, }
Endnote
%0 Conference Proceedings %A Hauschild, Anne-Christin %A Baumbach, Jörg Ingo %A Baumbach, Jan %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations %T Novel Developments In Computational Clinical Breath Analysis and Biomarker Detection : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002A-06CD-3 %D 2014 %B The 13th European Conference on Computational Biology %Z date of event: 2014-09-07 - 2014-09-10 %C Strasbourg, France %B ECCB'14 Highlight Papers Abstracts %Z sequence number: HP09 %U http://www.ebi.ac.uk/eccb/2014/eccb14.loria.fr/program/highlight-papers.html
98. Hildebrandt AK, Dietzen M, Lengauer T, Lenhof H-P, Althaus E, Hildebrandt A: Efficient Computation of Root Mean Square Deviations Under Rigid Transformations. Journal of Computational Chemistry 2014, 35.
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@article{HildebrandtJCC2014, TITLE = {Efficient Computation of Root Mean Square Deviations Under Rigid Transformations}, AUTHOR = {Hildebrandt, Anna K. and Dietzen, Matthias and Lengauer, Thomas and Lenhof, Hans-Peter and Althaus, Ernst and Hildebrandt, Andreas}, LANGUAGE = {eng}, ISSN = {0192-8651}, DOI = {10.1002/jcc.23513}, PUBLISHER = {Wiley}, ADDRESS = {New York, NY}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, JOURNAL = {Journal of Computational Chemistry}, VOLUME = {35}, NUMBER = {10}, PAGES = {765--771}, }
Endnote
%0 Journal Article %A Hildebrandt, Anna K. %A Dietzen, Matthias %A Lengauer, Thomas %A Lenhof, Hans-Peter %A Althaus, Ernst %A Hildebrandt, Andreas %+ External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations %T Efficient Computation of Root Mean Square Deviations Under Rigid Transformations : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-3E35-B %F ISI: 000332446300001 %R 10.1002/jcc.23513 %7 2013-12-19 %D 2014 %J Journal of Computational Chemistry %O J. Comput. Chem. %V 35 %N 10 %& 765 %P 765 - 771 %I Wiley %C New York, NY %@ false
99. Ibragimov R: Exact and Heuristic Algorithms for Network Alignment using Graph Edit Distance Models. Universität des Saarlandes; 2014.
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@phdthesis{Ibragimovphd14, TITLE = {Exact and Heuristic Algorithms for Network Alignment using Graph Edit Distance Models}, AUTHOR = {Ibragimov, Rashid}, LANGUAGE = {eng}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, }
Endnote
%0 Thesis %A Ibragimov, Rashid %Y Baumbach, Jan %A referee: Guo, Jiong %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society International Max Planck Research School, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T Exact and Heuristic Algorithms for Network Alignment using Graph Edit Distance Models : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0029-6E4C-7 %I Universität des Saarlandes %C Saarbrücken %D 2014 %P 149 p. %V phd %9 phd %U http://scidok.sulb.uni-saarland.de/volltexte/2015/5999/http://scidok.sulb.uni-saarland.de/doku/urheberrecht.php?la=de
100. Jalali A, Pfeifer N: Interpretable Per Case Weighted Ensemble Method for Cancer Associations. In Algorithms in Bioinformatics (WABI 2014). Springer; 2014. [Lecture Notes in Bioinformatics]
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@inproceedings{JalaliPfeifer2014, TITLE = {Interpretable Per Case Weighted Ensemble Method for Cancer Associations}, AUTHOR = {Jalali, Adrin and Pfeifer, Nico}, LANGUAGE = {eng}, ISBN = {978-3-662-44752-9}, DOI = {10.1007/978-3-662-44753-6_26}, PUBLISHER = {Springer}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, BOOKTITLE = {Algorithms in Bioinformatics (WABI 2014)}, EDITOR = {Brown, Dan and Morgenstern, Burkhard}, PAGES = {352--353}, SERIES = {Lecture Notes in Bioinformatics}, VOLUME = {8701}, ADDRESS = {Wroclaw, Poland}, }
Endnote
%0 Conference Proceedings %A Jalali, Adrin %A Pfeifer, Nico %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Interpretable Per Case Weighted Ensemble Method for Cancer Associations : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-901E-8 %R 10.1007/978-3-662-44753-6_26 %D 2014 %B 14th International Workshop on Algorithms in Bioinformatic %Z date of event: 2014-09-08 - 2014-09-10 %C Wroclaw, Poland %B Algorithms in Bioinformatics %E Brown, Dan; Morgenstern, Burkhard %P 352 - 353 %I Springer %@ 978-3-662-44752-9 %B Lecture Notes in Bioinformatics %N 8701
101. Jalali A, Pfeifer N: Interpretable Per Case Weighted Ensemble Method for Cancer Associations. BMC Genomics 2014, 17.
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@article{JalaliPfeifer2016, TITLE = {Interpretable Per Case Weighted Ensemble Method for Cancer Associations}, AUTHOR = {Jalali, Adrin and Pfeifer, Nico}, LANGUAGE = {eng}, ISSN = {1471-2164}, DOI = {10.1186/s12864-016-2647-9}, PUBLISHER = {BioMed Central}, ADDRESS = {London}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, JOURNAL = {BMC Genomics}, VOLUME = {17}, EID = {501}, }
Endnote
%0 Journal Article %A Jalali, Adrin %A Pfeifer, Nico %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Interpretable Per Case Weighted Ensemble Method for Cancer Associations : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002B-16A3-D %R 10.1186/s12864-016-2647-9 %7 2014 %D 2014 %J BMC Genomics %V 17 %Z sequence number: 501 %I BioMed Central %C London %@ false
102. Kalaghatgi P, Lawyer G, Lengauer T: Estimating HIV Epidemic Characteristics from a Dated Transmission Network. In Reviews in Antiviral Therapy & Infectious Diseases. Virology Education; 2014.
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@inproceedings{Kalaghatgi2014Talk, TITLE = {Estimating {HIV} epidemic characteristics from a dated transmission network}, AUTHOR = {Kalaghatgi, Prabhav and Lawyer, Glenn and Lengauer, Thomas}, LANGUAGE = {eng}, PUBLISHER = {Virology Education}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, BOOKTITLE = {Abstract Book 12th European Workshop on HIV \& Hepatitis Treatment Strategies \& Antiviral Drug Resistance}, PAGES = {3--3}, EID = {O-01}, JOURNAL = {Reviews in Antiviral Therapy \& Infectious Diseases}, VOLUME = {14-2}, ADDRESS = {Barcelona, Spain}, }
Endnote
%0 Conference Proceedings %A Kalaghatgi, Prabhav %A Lawyer, Glenn %A Lengauer, Thomas %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Estimating HIV Epidemic Characteristics from a Dated Transmission Network : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-6F33-C %D 2014 %B 12th European HIV & Hepatitis Workshop %Z date of event: 2014-03-26 - 2014-03-28 %C Barcelona, Spain %B Abstract Book 12th European Workshop on HIV & Hepatitis Treatment Strategies & Antiviral Drug Resistance %P 3 - 3 %Z sequence number: O-01 %I Virology Education %J Reviews in Antiviral Therapy & Infectious Diseases %V 14-2
103. Kalinina OV, Lengauer T: Protein Structure Prediction and Databases. eLS 2014.
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@article{Kalinina2014, TITLE = {Protein Structure Prediction and Databases}, AUTHOR = {Kalinina, Olga V. and Lengauer, Thomas}, LANGUAGE = {eng}, DOI = {10.1002/9780470015902.a0006214.pub2}, PUBLISHER = {Wiley}, ADDRESS = {Chichester}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, JOURNAL = {eLS}, PAGES = {1--5}, }
Endnote
%0 Journal Article %A Kalinina, Olga V. %A Lengauer, Thomas %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Protein Structure Prediction and Databases : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-6169-6 %R 10.1002/9780470015902.a0006214.pub2 %7 2014-09-15 %D 2014 %8 15.09.2014 %J eLS %& 1 %P 1 - 5 %I Wiley %C Chichester
104. Kreuer S, Hauschild A-C, Fink T, Baumbach JI, Maddula S, Volk T: Two Different Approaches for Pharmacokinetic Modeling of Exhaled Drug Concentrations. Scientific Reports 2014, 4.
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@article{HauschildScientificReports2014, TITLE = {Two Different Approaches for Pharmacokinetic Modeling of Exhaled Drug Concentrations}, AUTHOR = {Kreuer, S. and Hauschild, Anne-Christin and Fink, T. and Baumbach, J. I. and Maddula, S. and Volk, Th}, LANGUAGE = {eng}, DOI = {10.1038/srep05423}, PUBLISHER = {Nature Publishing Group}, ADDRESS = {London, UK}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, JOURNAL = {Scientific Reports}, VOLUME = {4}, EID = {5423}, }
Endnote
%0 Journal Article %A Kreuer, S. %A Hauschild, Anne-Christin %A Fink, T. %A Baumbach, J. I. %A Maddula, S. %A Volk, Th %+ External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations %T Two Different Approaches for Pharmacokinetic Modeling of Exhaled Drug Concentrations : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-8071-7 %F ISI: 000337889800002 %R 10.1038/srep05423 %7 2014 %D 2014 %J Scientific Reports %O Sci. Rep. %V 4 %Z sequence number: 5423 %I Nature Publishing Group %C London, UK %U http://www.nature.com/srep/2014/140624/srep05423/pdf/srep05423.pdf
105. Lengauer T, Pfeifer N, Kaiser R: Personalized HIV Therapy to Control Drug Resistance. Drug Discovery Today: Technologies 2014, 11.
Abstract
The therapy of HIV patients is characterized by both the high genomic diversity of the virus population harbored by the patient and a substantial volume of therapy options. The virus population is unique for each patient and time point. The large number of therapy options makes it difficult to select an optimal or near optimal therapy, especially with therapy-experienced patients. In the past decade, computer-based support for therapy selection, which assesses the level of viral resistance against drugs has become a mainstay for HIV patients. We discuss the properties of available systems and the perspectives of the field.
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@article{Lengauer2014DDT, TITLE = {Personalized {HIV} Therapy to Control Drug Resistance}, AUTHOR = {Lengauer, Thomas and Pfeifer, Nico and Kaiser, Rolf}, LANGUAGE = {eng}, ISSN = {17406749}, DOI = {10.1016/j.ddtec.2014.02.004}, PUBLISHER = {Elsevier}, ADDRESS = {Amsterdam}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, ABSTRACT = {The therapy of HIV patients is characterized by both the high genomic diversity of the virus population harbored by the patient and a substantial volume of therapy options. The virus population is unique for each patient and time point. The large number of therapy options makes it difficult to select an optimal or near optimal therapy, especially with therapy-experienced patients. In the past decade, computer-based support for therapy selection, which assesses the level of viral resistance against drugs has become a mainstay for HIV patients. We discuss the properties of available systems and the perspectives of the field.}, JOURNAL = {Drug Discovery Today: Technologies}, VOLUME = {11}, PAGES = {57--64}, }
Endnote
%0 Journal Article %A Lengauer, Thomas %A Pfeifer, Nico %A Kaiser, Rolf %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T Personalized HIV Therapy to Control Drug Resistance : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-8FDD-0 %R 10.1016/j.ddtec.2014.02.004 %7 2014 %D 2014 %X The therapy of HIV patients is characterized by both the high genomic diversity of the virus population harbored by the patient and a substantial volume of therapy options. The virus population is unique for each patient and time point. The large number of therapy options makes it difficult to select an optimal or near optimal therapy, especially with therapy-experienced patients. In the past decade, computer-based support for therapy selection, which assesses the level of viral resistance against drugs has become a mainstay for HIV patients. We discuss the properties of available systems and the perspectives of the field. %J Drug Discovery Today: Technologies %V 11 %& 57 %P 57 - 64 %I Elsevier %C Amsterdam %@ false
106. List M, Hauschild A-C, Tan O, Kruse TA, Mollenhauer J, Baumbach J, Batra R: Classification of Breast Cancer Subtypes by combining Gene Expression and DNA Methylation Data. Journal of Integrative Bioinformatics 2014, 11.
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@article{ListJIB2014, TITLE = {Classification of Breast Cancer Subtypes by combining Gene Expression and {DNA} Methylation Data}, AUTHOR = {List, Markus and Hauschild, Anne-Christin and Tan, Oihua and Kruse, Torben A. and Mollenhauer, Jan and Baumbach, Jan and Batra, Richa}, LANGUAGE = {eng}, ISSN = {1613-4516}, DOI = {10.2390/biecoll-jib-2014-236}, PUBLISHER = {Universit{\"a}t Bielefeld}, ADDRESS = {Bielefeld}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, JOURNAL = {Journal of Integrative Bioinformatics}, VOLUME = {11}, NUMBER = {2}, }
Endnote
%0 Journal Article %A List, Markus %A Hauschild, Anne-Christin %A Tan, Oihua %A Kruse, Torben A. %A Mollenhauer, Jan %A Baumbach, Jan %A Batra, Richa %+ External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations %T Classification of Breast Cancer Subtypes by combining Gene Expression and DNA Methylation Data : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002A-06F4-9 %R 10.2390/biecoll-jib-2014-236 %7 2014 %D 2014 %J Journal of Integrative Bioinformatics %O JIB %V 11 %N 2 %I Universität Bielefeld %C Bielefeld %@ false %U http://biecoll.ub.uni-bielefeld.de/volltexte/2014/5317
107. Maurer F, Hauschild A-C, Eisinger K, Baumbach J, Mayor A, Baumbach JI: MIMA - A Software for Analyte Identification in MCC/IMS Chromatograms by Mapping Accompanying GC/MS Measurements. International Journal for Ion Mobility Spectrometry 2014, 17.
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@article{Hauschild2014a, TITLE = {{MIMA} -- A Software for Analyte Identification in {MCC/IMS} Chromatograms by Mapping Accompanying {GC/MS} Measurements}, AUTHOR = {Maurer, Felix and Hauschild, Anne-Christin and Eisinger, Kathrin and Baumbach, Jan and Mayor, Arno and Baumbach, J{\"o}rg Ingo}, LANGUAGE = {eng}, ISSN = {1435-6163; 1865-4584}, DOI = {10.1007/s12127-014-0149-5}, PUBLISHER = {Springer}, ADDRESS = {New York, NY}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, JOURNAL = {International Journal for Ion Mobility Spectrometry}, VOLUME = {17}, NUMBER = {2}, PAGES = {95--101}, }
Endnote
%0 Journal Article %A Maurer, Felix %A Hauschild, Anne-Christin %A Eisinger, Kathrin %A Baumbach, Jan %A Mayor, Arno %A Baumbach, Jörg Ingo %+ External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations %T MIMA - A Software for Analyte Identification in MCC/IMS Chromatograms by Mapping Accompanying GC/MS Measurements : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0019-83B8-9 %R 10.1007/s12127-014-0149-5 %7 2014-04-05 %D 2014 %J International Journal for Ion Mobility Spectrometry %V 17 %N 2 %& 95 %P 95 - 101 %I Springer %C New York, NY %@ false
108. Metzler S: Identification of Gene Transfer Events in Viruses. Universität des Saarlandes; 2014.
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@mastersthesis{Metzler2014, TITLE = {Identification of Gene Transfer Events in Viruses}, AUTHOR = {Metzler, Saskia}, LANGUAGE = {eng}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, }
Endnote
%0 Thesis %A Metzler, Saskia %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Identification of Gene Transfer Events in Viruses : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-C282-6 %I Universität des Saarlandes %C Saarbrücken %D 2014 %V master %9 master
109. Metzler S, Kalinina OV: Detection of Atypical Genes in Virus Families Using a One-class SVM. BMC Genomics 2014, 15.
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@article{metzler2014detection, TITLE = {Detection of Atypical Genes in Virus Families Using a One-class {SVM}}, AUTHOR = {Metzler, Saskia and Kalinina, Olga V.}, ISSN = {1471-2164}, URL = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4210486&tool=pmcentrez&rendertype=abstract}, DOI = {10.1186/1471-2164-15-913}, PUBLISHER = {BioMed Central}, ADDRESS = {London}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, JOURNAL = {BMC Genomics}, VOLUME = {15}, NUMBER = {1}, EID = {913}, }
Endnote
%0 Journal Article %A Metzler, Saskia %A Kalinina, Olga V. %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Detection of Atypical Genes in Virus Families Using a One-class SVM : %U http://hdl.handle.net/11858/00-001M-0000-0024-5513-5 %F OTHER: accessionPMC4210486 %F OTHER: pmcidPMC4210486 %F OTHER: pmc-uid4210486 %F OTHER: publisher-id6601 %R 10.1186/1471-2164-15-913 %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4210486&tool=pmcentrez&rendertype=abstract %7 2014-10-20 %D 2014 %8 20.10.2014 %K SVM %J BMC Genomics %V 15 %N 1 %Z sequence number: 913 %I BioMed Central %C London %@ false
110. Morris JH, Wu A, Doncheva NT, Albrecht M, Ferrin TE: SetsApp: Set operations for Cytoscape Nodes and Edges. Faculty of 1000 Research 2014, 3.
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@article{doncheva14b, TITLE = {{setsApp}: Set operations for {Cytoscape} Nodes and Edges}, AUTHOR = {Morris, John H and Wu, Allan and Doncheva, Nadezhda Tsankova and Albrecht, Mario and Ferrin, Thomas E}, LANGUAGE = {eng}, URL = {http://f1000research.com/articles/3-149/v1}, PUBLISHER = {BioMed Central}, ADDRESS = {London}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, JOURNAL = {Faculty of 1000 Research}, VOLUME = {3}, PAGES = {1--10}, EID = {149}, }
Endnote
%0 Journal Article %A Morris, John H %A Wu, Allan %A Doncheva, Nadezhda Tsankova %A Albrecht, Mario %A Ferrin, Thomas E %+ External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations %T SetsApp: Set operations for Cytoscape Nodes and Edges : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-5D6D-A %U http://f1000research.com/articles/3-149/v1 %7 2014 %D 2014 %J Faculty of 1000 Research %O F1000Research %V 3 %& 1 %P 1 - 10 %Z sequence number: 149 %I BioMed Central %C London
111. Neumann-Fraune M, Beggel B, Kaiser R, Obermeier M: Hepatitis B Virus Drug Resistance Tools: One Sequence, Two Predictions. Intervirology 2014, 57.
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@article{Neumann-Fraune2014, TITLE = {Hepatitis {B} Virus Drug Resistance Tools: {One} Sequence, Two Predictions}, AUTHOR = {Neumann-Fraune, Maria and Beggel, Bastian and Kaiser, Rolf and Obermeier, Martin}, LANGUAGE = {eng}, ISSN = {0300-5526}, DOI = {10.1159/000361076}, PUBLISHER = {Karger}, ADDRESS = {Basel}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, JOURNAL = {Intervirology}, VOLUME = {57}, NUMBER = {3-4}, PAGES = {232--236}, }
Endnote
%0 Journal Article %A Neumann-Fraune, Maria %A Beggel, Bastian %A Kaiser, Rolf %A Obermeier, Martin %+ external Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society external external %T Hepatitis B Virus Drug Resistance Tools: One Sequence, Two Predictions : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-3CF5-2 %F ISI: 000339137300015 %R 10.1159/000361076 %D 2014 %J Intervirology %V 57 %N 3-4 %& 232 %P 232 - 236 %I Karger %C Basel %@ false
112. Nikumbh SP, Ghosh S, Jayaraman VK: Biogeography-Based Optimization for Dynamic Optimization of Chemical Reactors. In Applications of Metaheuristics in Process Engineering. Berlin: Springer; 2014.
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@incollection{Nikumbh2014, TITLE = {Biogeography-Based Optimization for Dynamic Optimization of Chemical Reactors}, AUTHOR = {Nikumbh, Sarvesh Prakash and Ghosh, Shameek and Jayaraman, Valadi K.}, LANGUAGE = {eng}, ISBN = {978-3-319-06507-6}, DOI = {10.1007/978-3-319-06508-3_8}, PUBLISHER = {Springer}, ADDRESS = {Berlin}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, BOOKTITLE = {Applications of Metaheuristics in Process Engineering}, EDITOR = {Valadi, Jayaraman and Siarry, Patrick}, PAGES = {201--216}, }
Endnote
%0 Book Section %A Nikumbh, Sarvesh Prakash %A Ghosh, Shameek %A Jayaraman, Valadi K. %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations %T Biogeography-Based Optimization for Dynamic Optimization of Chemical Reactors : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-8F17-E %R 10.1007/978-3-319-06508-3_8 %D 2014 %B Applications of Metaheuristics in Process Engineering %E Valadi, Jayaraman; Siarry, Patrick %P 201 - 216 %I Springer %C Berlin %@ 978-3-319-06507-6
113. O’Neill K, Jalali A, Aghaeepour N, Hoos H, Brinkman RR: Enhanced flowType/RchyOptimyx: a Bioconductor Pipeline for Discovery in High-dimensional Cytometry Data. Bioinformatics 2014, 30.
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@article{JalaliBioinformatics2014, TITLE = {Enhanced {flowType/RchyOptimyx}: a {B}ioconductor Pipeline for Discovery in High-dimensional Cytometry Data}, AUTHOR = {O'Neill, Kieran and Jalali, Adrin and Aghaeepour, Nima and Hoos, Holger and Brinkman, Ryan R.}, LANGUAGE = {eng}, ISSN = {1367-4803}, DOI = {10.1093/bioinformatics/btt770}, PUBLISHER = {Oxford University Press}, ADDRESS = {Oxford, UK}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, JOURNAL = {Bioinformatics}, VOLUME = {30}, NUMBER = {9}, PAGES = {1329--1330}, }
Endnote
%0 Journal Article %A O'Neill, Kieran %A Jalali, Adrin %A Aghaeepour, Nima %A Hoos, Holger %A Brinkman, Ryan R. %+ External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations %T Enhanced flowType/RchyOptimyx: a Bioconductor Pipeline for Discovery in High-dimensional Cytometry Data : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-809B-B %F ISI: 000336095100031 %R 10.1093/bioinformatics/btt770 %7 2014 %D 2014 %J Bioinformatics %V 30 %N 9 %& 1329 %P 1329 - 1330 %I Oxford University Press %C Oxford, UK %@ false
114. Pfeifer N, Walter H, Lengauer T: Association Between HIV-1 Coreceptor Usage and Resistance to Broadly Neutralizing Antibodies. Journal of Acquired Immune Deficiency Syndromes : JAIDS 2014, 67.
Abstract
Background: Recently discovered broadly neutralizing antibodies have revitalized hopes of developing a universal vaccine against HIV-1. Mainly responsible for new infections are variants only using CCR5 for cell entry, whereas CXCR4-using variants can become dominant in later infection stages. Methods: We performed a statistical analysis on two different previously published data sets. The first data set was a panel of 199 diverse HIV-1 isolates for which IC50 neutralization titers were determined for the broadly neutralizing antibodies VRC01, VRC-PG04, PG9, and PG16. The second data set contained env sequences of viral variants extracted from HIV-1–infected humanized mice treated with the antibody PGT128 and from untreated control mice. Results: For the panel of 199 diverse HIV-1 isolates, we found a statistically significant association between viral resistance to PG9 and PG16 and CXCR4 coreceptor usage (P = 0.0011 and P = 0.0010, respectively). Our analysis of viral variants from HIV-1–infected humanized mice under treatment with the broadly neutralizing antibody PGT128 indicated that certain antibodies might drive a viral population toward developing CXCR4 coreceptor usage capability (P = 0.0011 for the comparison between PGT128 and control measurement). Conclusions: These analyses highlight the importance of accounting for a possible coreceptor usage bias pertaining to the effectiveness of an HIV vaccine and to passive antibody transfer as therapeutic approach.
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@article{PfeiferJAIDS2014, TITLE = {Association Between {HIV}-1 Coreceptor Usage and Resistance to Broadly Neutralizing Antibodies}, AUTHOR = {Pfeifer, Nico and Walter, Hauke and Lengauer, Thomas}, LANGUAGE = {eng}, DOI = {10.1097/QAI.0000000000000283}, PUBLISHER = {Lippincott Williams \& Wilkins}, ADDRESS = {Philadelphia, PA}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014-10-01}, ABSTRACT = {Background: Recently discovered broadly neutralizing antibodies have revitalized hopes of developing a universal vaccine against HIV-1. Mainly responsible for new infections are variants only using CCR5 for cell entry, whereas CXCR4-using variants can become dominant in later infection stages. Methods: We performed a statistical analysis on two different previously published data sets. The first data set was a panel of 199 diverse HIV-1 isolates for which IC50 neutralization titers were determined for the broadly neutralizing antibodies VRC01, VRC-PG04, PG9, and PG16. The second data set contained env sequences of viral variants extracted from HIV-1--infected humanized mice treated with the antibody PGT128 and from untreated control mice. Results: For the panel of 199 diverse HIV-1 isolates, we found a statistically significant association between viral resistance to PG9 and PG16 and CXCR4 coreceptor usage (P = 0.0011 and P = 0.0010, respectively). Our analysis of viral variants from HIV-1--infected humanized mice under treatment with the broadly neutralizing antibody PGT128 indicated that certain antibodies might drive a viral population toward developing CXCR4 coreceptor usage capability (P = 0.0011 for the comparison between PGT128 and control measurement). Conclusions: These analyses highlight the importance of accounting for a possible coreceptor usage bias pertaining to the effectiveness of an HIV vaccine and to passive antibody transfer as therapeutic approach.}, JOURNAL = {Journal of Acquired Immune Deficiency Syndromes : JAIDS}, VOLUME = {67}, NUMBER = {2}, PAGES = {107--112}, }
Endnote
%0 Journal Article %A Pfeifer, Nico %A Walter, Hauke %A Lengauer, Thomas %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Association Between HIV-1 Coreceptor Usage and Resistance to Broadly Neutralizing Antibodies : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-5527-A %R 10.1097/QAI.0000000000000283 %2 PMC4175123 %7 2014-09-24 %D 2014 %8 01.10.2014 %X Background: Recently discovered broadly neutralizing antibodies have revitalized hopes of developing a universal vaccine against HIV-1. Mainly responsible for new infections are variants only using CCR5 for cell entry, whereas CXCR4-using variants can become dominant in later infection stages. Methods: We performed a statistical analysis on two different previously published data sets. The first data set was a panel of 199 diverse HIV-1 isolates for which IC50 neutralization titers were determined for the broadly neutralizing antibodies VRC01, VRC-PG04, PG9, and PG16. The second data set contained env sequences of viral variants extracted from HIV-1–infected humanized mice treated with the antibody PGT128 and from untreated control mice. Results: For the panel of 199 diverse HIV-1 isolates, we found a statistically significant association between viral resistance to PG9 and PG16 and CXCR4 coreceptor usage (P = 0.0011 and P = 0.0010, respectively). Our analysis of viral variants from HIV-1–infected humanized mice under treatment with the broadly neutralizing antibody PGT128 indicated that certain antibodies might drive a viral population toward developing CXCR4 coreceptor usage capability (P = 0.0011 for the comparison between PGT128 and control measurement). Conclusions: These analyses highlight the importance of accounting for a possible coreceptor usage bias pertaining to the effectiveness of an HIV vaccine and to passive antibody transfer as therapeutic approach. %J Journal of Acquired Immune Deficiency Syndromes : JAIDS %V 67 %N 2 %& 107 %P 107 - 112 %I Lippincott Williams & Wilkins %C Philadelphia, PA
115. Pironti A, Pfeifer N, Kaiser R, Walter H, Lengauer T: Accurate Prediction of Drug-exposure Without Using Established Drug-resistance Mutations. Antiviral Therapy 2014.
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@inproceedings{Pironti2013b, TITLE = {Accurate Prediction of Drug-exposure Without Using Established Drug-resistance Mutations}, AUTHOR = {Pironti, Alejandro and Pfeifer, Nico and Kaiser, Rolf and Walter, Hauke and Lengauer, Thomas}, LANGUAGE = {eng}, ISSN = {1359-6535}, PUBLISHER = {International Medical Press}, PUBLISHER = {International Medical Press}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, BOOKTITLE = {Abstracts presented at the International Workshop on Antiviral Drug Resistance: Meeting the Global Challenge}, JOURNAL = {Antiviral Therapy}, VOLUME = {19}, ISSUE = {Suppl. 1}, EID = {A75}, ADDRESS = {Berlin, Germany}, }
Endnote
%0 Generic %A Pironti, Alejandro %A Pfeifer, Nico %A Kaiser, Rolf %A Walter, Hauke %A Lengauer, Thomas %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Accurate Prediction of Drug-exposure Without Using Established Drug-resistance Mutations : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-667A-5 %D 2014 %Z name of event: International Workshop on Antiviral Drug Resistance: Meeting the Global Challenge %Z date of event: 2014-06-03 - 2014-06-07 %Z place of event: Berlin, Germany %B Abstracts presented at the International Workshop on Antiviral Drug Resistance: Meeting the Global Challenge %J Antiviral Therapy %V 19 %N Suppl. 1 %Z sequence number: A75 %@ false
116. Pironti A, Pfeifer N, Kaiser R, Walter H, Lengauer T: Improved HIV-1 Drug-exposure Reconstruction with Linear Support Vector Machines. In Reviews in Antiviral Therapy & Infectious Diseases. Virology Education; 2014.
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@inproceedings{Pironti2014z, TITLE = {Improved {HIV}-1 Drug-exposure Reconstruction with Linear Support Vector Machines}, AUTHOR = {Pironti, Alejandro and Pfeifer, Nico and Kaiser, Rolf and Walter, Hauke and Lengauer, Thomas}, LANGUAGE = {eng}, PUBLISHER = {Virology Education}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, BOOKTITLE = {Abstract Book 12th European Workshop on HIV \& Hepatitis Treatment Strategies \& Antiviral Drug Resistance}, PAGES = {67--67}, EID = {P-55}, JOURNAL = {Reviews in Antiviral Therapy \& Infectious Diseases}, VOLUME = {14-2}, ADDRESS = {Barcelona, Spain}, }
Endnote
%0 Conference Proceedings %A Pironti, Alejandro %A Pfeifer, Nico %A Kaiser, Rolf %A Walter, Hauke %A Lengauer, Thomas %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Improved HIV-1 Drug-exposure Reconstruction with Linear Support Vector Machines : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-6681-4 %D 2014 %B 12th European HIV & Hepatitis Workshop %Z date of event: 2014-03-26 - 2014-03-28 %C Barcelona, Spain %B Abstract Book 12th European Workshop on HIV & Hepatitis Treatment Strategies & Antiviral Drug Resistance %P 67 - 67 %Z sequence number: P-55 %I Virology Education %J Reviews in Antiviral Therapy & Infectious Diseases %V 14-2
117. Pironti A, Sierra S, Kaiser R, Lengauer T, Pfeifer N: Simulation of Sanger-sequencing Errors in the Context of Genotypic Tropism Determination. Antiviral Therapy 2014.
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@inproceedings{Pironti2013c, TITLE = {Simulation of {S}anger-sequencing Errors in the Context of Genotypic Tropism Determination}, AUTHOR = {Pironti, Alejandro and Sierra, Saleta and Kaiser, Rolf and Lengauer, Thomas and Pfeifer, Nico}, LANGUAGE = {eng}, ISSN = {1359-6535}, PUBLISHER = {International Medical Press}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, BOOKTITLE = {Abstracts presented at the International Workshop on Antiviral Drug Resistance: Meeting the Global Challenge}, EID = {A81}, JOURNAL = {Antiviral Therapy}, VOLUME = {19}, ISSUE = {Supplement 1}, }
Endnote
%0 Generic %A Pironti, Alejandro %A Sierra, Saleta %A Kaiser, Rolf %A Lengauer, Thomas %A Pfeifer, Nico %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Simulation of Sanger-sequencing Errors in the Context of Genotypic Tropism Determination : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-668A-1 %D 2014 %B Abstracts presented at the International Workshop on Antiviral Drug Resistance: Meeting the Global Challenge %Z sequence number: A81 %J Antiviral Therapy %V 19 %N Supplement 1 %@ false
118. Pironti A, Pfeifer N, Kaiser R, Walter H, Lengauer T: Improved Therapy-success Prediction with GSS Estimated from Clinical HIV-1 Sequences. Journal of the International AIDS Society (Proc HIV Glasgow 2014) 2014, 17(Suppl 3).
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@article{Pironti2013d, TITLE = {Improved Therapy-success Prediction with {GSS} Estimated from Clinical {HIV}-1 Sequences}, AUTHOR = {Pironti, Alejandro and Pfeifer, Nico and Kaiser, Rolf and Walter, Hauke and Lengauer, Thomas}, LANGUAGE = {eng}, PUBLISHER = {International AIDS Society}, ADDRESS = {Geneva}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, JOURNAL = {Journal of the International AIDS Society (Proc. HIV Glasgow)}, VOLUME = {17}, NUMBER = {Suppl 3}, EID = {19743}, BOOKTITLE = {Abstract Supplement of the HIV Drug Therapy Glasgow Congress 2014 (HIV Glasgow 2014)}, EDITOR = {Kippax, Susan and Sow, Papa Salif and Wainberg, Marc}, }
Endnote
%0 Journal Article %A Pironti, Alejandro %A Pfeifer, Nico %A Kaiser, Rolf %A Walter, Hauke %A Lengauer, Thomas %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Improved Therapy-success Prediction with GSS Estimated from Clinical HIV-1 Sequences : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-66A7-1 %7 2014-11-02 %D 2014 %8 02.11.2014 %J Journal of the International AIDS Society %V 17 %N Suppl 3 %Z sequence number: 19743 %I International AIDS Society %C Geneva %B Abstract Supplement of the HIV Drug Therapy Glasgow Congress 2014 %O HIV Glasgow 2014
119. Planello AC, Ji J, Sharma V, Singhania R, Mbabaali F, Müller F, Alfaro JA, Bock C, De Carvalho DD, Batada NN: Aberrant DNA Methylation Reprogramming During Induced Pluripotent Stem Cell Generation is Dependent on the Choice of Reprogramming Factors. Cell Regeneration 2014, 3.
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@article{BockAberrant2014, TITLE = {Aberrant {DNA} Methylation Reprogramming During Induced Pluripotent Stem Cell Generation is Dependent on the Choice of Reprogramming Factors}, AUTHOR = {Planello, Aline C. and Ji, Junfeng and Sharma, Vivek and Singhania, Rajat and Mbabaali, Faridah and M{\"u}ller, Fabian and Alfaro, Javier A. and Bock, Christoph and De Carvalho, Daniel D. and Batada, Nizar N.}, LANGUAGE = {eng}, ISSN = {2045-9769}, URL = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4230737&tool=pmcentrez&rendertype=abstract}, DOI = {10.1186/2045-9769-3-4}, PUBLISHER = {BioMed Central}, ADDRESS = {London}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, JOURNAL = {Cell Regeneration}, VOLUME = {3}, NUMBER = {1}, EID = {4}, }
Endnote
%0 Journal Article %A Planello, Aline C. %A Ji, Junfeng %A Sharma, Vivek %A Singhania, Rajat %A Mbabaali, Faridah %A Müller, Fabian %A Alfaro, Javier A. %A Bock, Christoph %A De Carvalho, Daniel D. %A Batada, Nizar N. %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations %T Aberrant DNA Methylation Reprogramming During Induced Pluripotent Stem Cell Generation is Dependent on the Choice of Reprogramming Factors : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-6BCF-C %F OTHER: accessionPMC4230737 %F OTHER: pmcidPMC4230737 %F OTHER: pmc-uid4230737 %F OTHER: publisher-id19 %R 10.1186/2045-9769-3-4 %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4230737&tool=pmcentrez&rendertype=abstract %7 2014-02-07 %D 2014 %8 07.02.2014 %J Cell Regeneration %V 3 %N 1 %Z sequence number: 4 %I BioMed Central %C London %@ false
120. Röttger R: Active Transitivity Clustering of Large-scale Biomedical Datasets. Universität des Saarlandes; 2014.
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@phdthesis{Roettger2014, TITLE = {Active Transitivity Clustering of Large-scale Biomedical Datasets}, AUTHOR = {R{\"o}ttger, Richard}, LANGUAGE = {eng}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, }
Endnote
%0 Thesis %A Röttger, Richard %A referee: Lengauer, Thomas %Y Baumbach, Jan %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society International Max Planck Research School, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Active Transitivity Clustering of Large-scale Biomedical Datasets : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-96BE-A %I Universität des Saarlandes %C Saarbrücken %D 2014 %P 215 p. %V phd %9 phd %U http://scidok.sulb.uni-saarland.de/doku/lic_ohne_pod.php?la=dehttp://scidok.sulb.uni-saarland.de/volltexte/2014/5809/
121. Schelhorn SE: Going Viral : an Integrated View on Virological Data Analysis from Basic Research to Clinical Applications. Universität des Saarlandes; 2014.
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@phdthesis{Schelhorn2014, TITLE = {Going Viral : an Integrated View on Virological Data Analysis from Basic Research to Clinical Applications}, AUTHOR = {Schelhorn, Sven Eric}, LANGUAGE = {eng}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, }
Endnote
%0 Thesis %A Schelhorn, Sven Eric %Y Lengauer, Thomas %A referee: Lenhof, Hans-Peter %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society International Max Planck Research School, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Algorithms and Complexity, MPI for Informatics, Max Planck Society %T Going Viral : an Integrated View on Virological Data Analysis from Basic Research to Clinical Applications : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-96C0-2 %I Universität des Saarlandes %C Saarbrücken %D 2014 %P 323 p. %V phd %9 phd %U http://scidok.sulb.uni-saarland.de/doku/lic_ohne_pod.php?la=dehttp://scidok.sulb.uni-saarland.de/volltexte/2014/5724/
122. Schulz MH: Letting the Data Speak for Themselves: a Fully Bayesian Approach to Transcriptome Assembly. Genome Biology 2014, 15.
Abstract
A novel method for transcriptome assembly, Bayesembler, provides greater accuracy without sacrifice of computational speed, and particular advantages for alternative transcripts expressed at low levels.
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@article{s13059-014-0498-8, TITLE = {Letting the Data Speak for Themselves: a Fully {B}ayesian Approach to Transcriptome Assembly}, AUTHOR = {Schulz, Marcel H.}, LANGUAGE = {eng}, ISSN = {1465-6906}, DOI = {10.1186/s13059-014-0498-8}, PUBLISHER = {BioMed Central Ltd.}, ADDRESS = {London}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, ABSTRACT = {A novel method for transcriptome assembly, Bayesembler, provides greater accuracy without sacrifice of computational speed, and particular advantages for alternative transcripts expressed at low levels.}, JOURNAL = {Genome Biology}, VOLUME = {15}, NUMBER = {10}, EID = {498}, }
Endnote
%0 Journal Article %A Schulz, Marcel H. %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Letting the Data Speak for Themselves: a Fully Bayesian Approach to Transcriptome Assembly : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-934A-8 %R 10.1186/s13059-014-0498-8 %7 2014-10-31 %D 2014 %X A novel method for transcriptome assembly, Bayesembler, provides greater accuracy without sacrifice of computational speed, and particular advantages for alternative transcripts expressed at low levels. %J Genome Biology %V 15 %N 10 %Z sequence number: 498 %I BioMed Central Ltd. %C London %@ false %U http://genomebiology.com/2014/15/10/498
123. Schulz MH, Weese D, Holtgrewe M, Dimitrova V, Niu S, Reinert K, Richard H: Fiona: A Parallel and Automatic Strategy for Read Error Correction. Bioinformatics (Proc ECCB 2014) 2014, 30.
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@article{SchulzBioinformatics2014, TITLE = {Fiona: A Parallel and Automatic Strategy for Read Error Correction}, AUTHOR = {Schulz, Marcel H. and Weese, David and Holtgrewe, Manuel and Dimitrova, Viktoria and Niu, Sijia and Reinert, Knut and Richard, Hugues}, LANGUAGE = {eng}, ISSN = {1367-4803}, DOI = {10.1093/bioinformatics/btu440}, PUBLISHER = {Oxford University Press}, ADDRESS = {Oxford}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, JOURNAL = {Bioinformatics (Proc. ECCB)}, VOLUME = {30}, NUMBER = {17}, PAGES = {I356--I363}, BOOKTITLE = {The 13th European Conference on Computational Biology (ECCB 2014)}, }
Endnote
%0 Journal Article %A Schulz, Marcel H. %A Weese, David %A Holtgrewe, Manuel %A Dimitrova, Viktoria %A Niu, Sijia %A Reinert, Knut %A Richard, Hugues %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations %T Fiona: A Parallel and Automatic Strategy for Read Error Correction : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-6C8D-7 %F ISI: 000342912400003 %R 10.1093/bioinformatics/btu440 %7 2014 %D 2014 %J Bioinformatics %V 30 %N 17 %& I356 %P I356 - I363 %I Oxford University Press %C Oxford %@ false %B The 13th European Conference on Computational Biology %O ECCB 2014 held from September 7 to 10, 2014 at the Congress Center of Strasbourg, France
124. Setty Y: In-silico Models of Stem Cell and Developmental Systems. Theoretical Biology & Medical Modelling 2014, 11.
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@article{SettyTBMM2014, TITLE = {In-silico Models of Stem Cell and Developmental Systems}, AUTHOR = {Setty, Yaki}, LANGUAGE = {eng}, ISSN = {1742-4682}, URL = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3896968&tool=pmcentrez&rendertype=abstract}, DOI = {10.1186/1742-4682-11-1}, PUBLISHER = {BioMed Central}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, JOURNAL = {Theoretical Biology \& Medical Modelling}, VOLUME = {11}, PAGES = {1--11}, EID = {1}, }
Endnote
%0 Journal Article %A Setty, Yaki %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T In-silico Models of Stem Cell and Developmental Systems : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-3D0D-F %F OTHER: accessionPMC3896968 %F OTHER: pmcidPMC3896968 %F OTHER: pmc-uid3896968 %F OTHER: publisher-id1742-4682-11-1 %R 10.1186/1742-4682-11-1 %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3896968&tool=pmcentrez&rendertype=abstract %7 2014-01-08 %D 2014 %8 08.01.2014 %J Theoretical Biology & Medical Modelling %O Theor Biol Med Model %V 11 %& 1 %P 1 - 11 %Z sequence number: 1 %I BioMed Central %@ false
125. Smolinska A, Hauschild A-C, Fijten R, Dallinga J, Baumbach J, van Schooten F: Current Breathomics - a Review on Data Pre-processing Techniques and Machine Learning in Metabolomics Breath Analysis. Journal of Breath Research 2014, 8.
Abstract
We define breathomics as the metabolomics study of exhaled air. It is a strongly emerging metabolomics research field that mainly focuses on health-related Volatile Organic Compounds (VOCs). Since the composition of these compounds varies depending on health status, breathomics holds great promise as non-invasive diagnostic tool. Thusthe main aim of breathomics is to find the patterns of VOCs relatedto deviant (for instance inflammatory) metabolic processes occurring e.g. inthe human body. Consequently, methods for recording VOCs in exhaledair for diagnosis and monitoring health status gained increased attentionover the last years. As a result, measuring breath air high-throughput and in high resolution has enormously developed. Yet machine learning solutions for fingerprinting VOCs profiles in the breathomics research field arestill in their infancy. Therefore in this review/tutorial we describe the current state of the art in data pre-processing and analysis. We start with detailed pre-processing pipelines for breathomics data obtained from Gas-Chromatography Mass Spectrometry and Ion Mobility Spectrometer coupled to Multi-Capillary Columns. The final result of such pipelines is a matrix containing the relative abundances of a set of VOCs for a group ofpatients under different conditions (e.g. disease stage, treatment). Independently of the utilized analytical technique the most important question: �Which VOCs are discriminatory�, remains the same. Hence, in the main part of our review/tutorial we focus on several modern machine learning methods (multivariate statistics). We demonstrate the advantages as well the drawbacks of such techniques. We aim to help the breath analysis community to understand when and how one can profitfrom a certain method. In parallel, we hope to make the community aware of the existing, yet in breathomics unmet research data fusion methods.
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@article{Hauschild2014, TITLE = {Current Breathomics -- a Review on Data Pre-processing Techniques and Machine Learning in Metabolomics Breath Analysis}, AUTHOR = {Smolinska, Agnieszka and Hauschild, Anne-Christin and Fijten, Rianne and Dallinga, Jan and Baumbach, Jan and van Schooten, Frederik}, LANGUAGE = {eng}, DOI = {10.1088/1752-7155/8/2/027105}, PUBLISHER = {IOP}, ADDRESS = {Bristol}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, ABSTRACT = {We define breathomics as the metabolomics study of exhaled air. It is a strongly emerging metabolomics research field that mainly focuses on health-related Volatile Organic Compounds (VOCs). Since the composition of these compounds varies depending on health status, breathomics holds great promise as non-invasive diagnostic tool. Thusthe main aim of breathomics is to find the patterns of VOCs relatedto deviant (for instance inflammatory) metabolic processes occurring e.g. inthe human body. Consequently, methods for recording VOCs in exhaledair for diagnosis and monitoring health status gained increased attentionover the last years. As a result, measuring breath air high-throughput and in high resolution has enormously developed. Yet machine learning solutions for fingerprinting VOCs profiles in the breathomics research field arestill in their infancy. Therefore in this review/tutorial we describe the current state of the art in data pre-processing and analysis. We start with detailed pre-processing pipelines for breathomics data obtained from Gas-Chromatography Mass Spectrometry and Ion Mobility Spectrometer coupled to Multi-Capillary Columns. The final result of such pipelines is a matrix containing the relative abundances of a set of VOCs for a group ofpatients under different conditions (e.g. disease stage, treatment). Independently of the utilized analytical technique the most important question: {\diamond}Which VOCs are discriminatory{\diamond}, remains the same. Hence, in the main part of our review/tutorial we focus on several modern machine learning methods (multivariate statistics). We demonstrate the advantages as well the drawbacks of such techniques. We aim to help the breath analysis community to understand when and how one can profitfrom a certain method. In parallel, we hope to make the community aware of the existing, yet in breathomics unmet research data fusion methods.}, JOURNAL = {Journal of Breath Research}, VOLUME = {8}, NUMBER = {2}, EID = {027105}, }
Endnote
%0 Journal Article %A Smolinska, Agnieszka %A Hauschild, Anne-Christin %A Fijten, Rianne %A Dallinga, Jan %A Baumbach, Jan %A van Schooten, Frederik %+ External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T Current Breathomics - a Review on Data Pre-processing Techniques and Machine Learning in Metabolomics Breath Analysis : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-66CC-F %R 10.1088/1752-7155/8/2/027105 %7 2014 %D 2014 %X We define breathomics as the metabolomics study of exhaled air. It is a strongly emerging metabolomics research field that mainly focuses on health-related Volatile Organic Compounds (VOCs). Since the composition of these compounds varies depending on health status, breathomics holds great promise as non-invasive diagnostic tool. Thusthe main aim of breathomics is to find the patterns of VOCs relatedto deviant (for instance inflammatory) metabolic processes occurring e.g. inthe human body. Consequently, methods for recording VOCs in exhaledair for diagnosis and monitoring health status gained increased attentionover the last years. As a result, measuring breath air high-throughput and in high resolution has enormously developed. Yet machine learning solutions for fingerprinting VOCs profiles in the breathomics research field arestill in their infancy. Therefore in this review/tutorial we describe the current state of the art in data pre-processing and analysis. We start with detailed pre-processing pipelines for breathomics data obtained from Gas-Chromatography Mass Spectrometry and Ion Mobility Spectrometer coupled to Multi-Capillary Columns. The final result of such pipelines is a matrix containing the relative abundances of a set of VOCs for a group ofpatients under different conditions (e.g. disease stage, treatment). Independently of the utilized analytical technique the most important question: �Which VOCs are discriminatory�, remains the same. Hence, in the main part of our review/tutorial we focus on several modern machine learning methods (multivariate statistics). We demonstrate the advantages as well the drawbacks of such techniques. We aim to help the breath analysis community to understand when and how one can profitfrom a certain method. In parallel, we hope to make the community aware of the existing, yet in breathomics unmet research data fusion methods. %J Journal of Breath Research %V 8 %N 2 %Z sequence number: 027105 %I IOP %C Bristol
126. Struck D, Lawyer G, Ternes A-M, Schmit J-C, Perez Bercoff D: COMET: Adaptive Context-based Modeling for Ultrafast HIV-1 Subtype Identification. Nucleic Acids Research 2014, 42.
Abstract
Viral sequence classification has wide applications in clinical, epidemiological, structural and functional categorization studies. Most existing approaches rely on an initial alignment step followed by classification based on phylogenetic or statistical algorithms. Here we present an ultrafast alignment-free subtyping tool for human immunodeficiency virus type one (HIV-1) adapted from Prediction by Partial Matching compression. This tool, named COMET, was compared to the widely used phylogeny-based REGA and SCUEAL tools using synthetic and clinical HIV data sets (1 090 698 and 10 625 sequences, respectively). COMET's sensitivity and specificity were comparable to or higher than the two other subtyping tools on both data sets for known subtypes. COMET also excelled in detecting and identifying new recombinant forms, a frequent feature of the HIV epidemic. Runtime comparisons showed that COMET was almost as fast as USEARCH. This study demonstrates the advantages of alignment-free classification of viral sequences, which feature high rates of variation, recombination and insertions/deletions. COMET is free to use via an online interface.
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@article{Struck2014, TITLE = {{COMET}: {A}daptive Context-based Modeling for Ultrafast {HIV}-1 Subtype Identification}, AUTHOR = {Struck, Daniel and Lawyer, Glenn and Ternes, Anne-Marie and Schmit, Jean-Claude and Perez Bercoff, Danielle}, ISSN = {0301-5610}, DOI = {10.1093/nar/gku739}, PUBLISHER = {Oxford University Press}, ADDRESS = {Oxford}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, DATE = {2014}, ABSTRACT = {Viral sequence classification has wide applications in clinical, epidemiological, structural and functional categorization studies. Most existing approaches rely on an initial alignment step followed by classification based on phylogenetic or statistical algorithms. Here we present an ultrafast alignment-free subtyping tool for human immunodeficiency virus type one (HIV-1) adapted from Prediction by Partial Matching compression. This tool, named COMET, was compared to the widely used phylogeny-based REGA and SCUEAL tools using synthetic and clinical HIV data sets (1 090 698 and 10 625 sequences, respectively). COMET's sensitivity and specificity were comparable to or higher than the two other subtyping tools on both data sets for known subtypes. COMET also excelled in detecting and identifying new recombinant forms, a frequent feature of the HIV epidemic. Runtime comparisons showed that COMET was almost as fast as USEARCH. This study demonstrates the advantages of alignment-free classification of viral sequences, which feature high rates of variation, recombination and insertions/deletions. COMET is free to use via an online interface.}, JOURNAL = {Nucleic Acids Research}, VOLUME = {42}, NUMBER = {18}, EID = {e144}, }
Endnote
%0 Journal Article %A Struck, Daniel %A Lawyer, Glenn %A Ternes, Anne-Marie %A Schmit, Jean-Claude %A Perez Bercoff, Danielle %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T COMET: Adaptive Context-based Modeling for Ultrafast HIV-1 Subtype Identification : %U http://hdl.handle.net/11858/00-001M-0000-0024-CA34-B %R 10.1093/nar/gku739 %D 2014 %X Viral sequence classification has wide applications in clinical, epidemiological, structural and functional categorization studies. Most existing approaches rely on an initial alignment step followed by classification based on phylogenetic or statistical algorithms. Here we present an ultrafast alignment-free subtyping tool for human immunodeficiency virus type one (HIV-1) adapted from Prediction by Partial Matching compression. This tool, named COMET, was compared to the widely used phylogeny-based REGA and SCUEAL tools using synthetic and clinical HIV data sets (1 090 698 and 10 625 sequences, respectively). COMET's sensitivity and specificity were comparable to or higher than the two other subtyping tools on both data sets for known subtypes. COMET also excelled in detecting and identifying new recombinant forms, a frequent feature of the HIV epidemic. Runtime comparisons showed that COMET was almost as fast as USEARCH. This study demonstrates the advantages of alignment-free classification of viral sequences, which feature high rates of variation, recombination and insertions/deletions. COMET is free to use via an online interface. %J Nucleic Acids Research %O Nucleic Acids Res. %V 42 %N 18 %Z sequence number: e144 %I Oxford University Press %C Oxford %@ false %U http://nar.oxfordjournals.org/content/early/2014/08/12/nar.gku739.abstract
127. Sun P, Speicher NK, Roettger R, Guo J, Baumbach J: Bi-Force: Large-scale Bicluster Editing and its Application to Gene Expression Data Biclustering. Nucleic Acids Research 2014, 42.
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@article{SunNAR2014, TITLE = {Bi-{Force}: {L}arge-scale bicluster editing and its application to gene expression data biclustering}, AUTHOR = {Sun, Peng and Speicher, Nora K. and Roettger, Richard and Guo, Jiong and Baumbach, Jan}, LANGUAGE = {eng}, ISSN = {0305-1048}, DOI = {10.1093/nar/gku201}, PUBLISHER = {Oxford University Press}, ADDRESS = {Oxford, UK}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, JOURNAL = {Nucleic Acids Research}, VOLUME = {42}, NUMBER = {9}, PAGES = {1--12}, EID = {e78}, }
Endnote
%0 Journal Article %A Sun, Peng %A Speicher, Nora K. %A Roettger, Richard %A Guo, Jiong %A Baumbach, Jan %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society external Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Bi-Force: Large-scale Bicluster Editing and its Application to Gene Expression Data Biclustering : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-3CEC-7 %F ISI: 000336495400005 %R 10.1093/nar/gku201 %7 2014 %D 2014 %J Nucleic Acids Research %O Nucleic Acids Res %V 42 %N 9 %& 1 %P 1 - 12 %Z sequence number: e78 %I Oxford University Press %C Oxford, UK %@ false %U http://dx.doi.org/10.1093/nar/gku201
128. Tobi EW, Goeman JJ, Monajemi R, Gu H, Putter H, Zhang Y, Slieker RC, Stok AP, Thijssen PE, Müller F, van Zwet EW, Bock C, Meissner A, Lumey LH, Eline Slagboom P, Heijmans BT: DNA Methylation Signatures Link Prenatal Famine Exposure to Growth and Metabolism. Nature Communications 2014, 5.
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@article{Tobi:2014br, TITLE = {{DNA} Methylation Signatures Link Prenatal Famine Exposure to Growth and Metabolism}, AUTHOR = {Tobi, Elmar W and Goeman, Jelle J and Monajemi, Ramin and Gu, Hongcang and Putter, Hein and Zhang, Yanju and Slieker, Roderick C and Stok, Arthur P and Thijssen, Peter E and M{\"u}ller, Fabian and van Zwet, Erik W and Bock, Christoph and Meissner, Alexander and Lumey, L H and Eline Slagboom, P and Heijmans, Bastiaan T}, LANGUAGE = {eng}, DOI = {10.1038/ncomms6592}, PUBLISHER = {Nature Publishing Group}, ADDRESS = {London}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, JOURNAL = {Nature Communications}, VOLUME = {5}, PAGES = {1--13}, EID = {5592}, }
Endnote
%0 Journal Article %A Tobi, Elmar W %A Goeman, Jelle J %A Monajemi, Ramin %A Gu, Hongcang %A Putter, Hein %A Zhang, Yanju %A Slieker, Roderick C %A Stok, Arthur P %A Thijssen, Peter E %A Müller, Fabian %A van Zwet, Erik W %A Bock, Christoph %A Meissner, Alexander %A Lumey, L H %A Eline Slagboom, P %A Heijmans, Bastiaan T %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations %T DNA Methylation Signatures Link Prenatal Famine Exposure to Growth and Metabolism : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-5D1A-4 %R 10.1038/ncomms6592 %7 2014 %D 2014 %J Nature Communications %V 5 %& 1 %P 1 - 13 %Z sequence number: 5592 %I Nature Publishing Group %C London %U http://www.nature.com/ncomms/2014/141126/ncomms6592/full/ncomms6592.html
129. Vu D, Szöke S, Wiwie C, Baumbach J, Cardinali G, Röttger R, Robert V: Massive Fungal Biodiversity Data Re-annotation with Multi-level Clustering. Scientific Reports 2014, 4.
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@article{DuanSR2014, TITLE = {Massive Fungal Biodiversity Data Re-annotation with Multi-level Clustering}, AUTHOR = {Vu, Duong and Sz{\"o}ke, Sz{\'a}niszl{\'o} and Wiwie, Christian and Baumbach, Jan and Cardinali, Gianluigi and R{\"o}ttger, Richard and Robert, Vincent}, LANGUAGE = {eng}, DOI = {10.1038/srep06837}, PUBLISHER = {Nature Publishing Group}, ADDRESS = {London, UK}, YEAR = {2014}, MARGINALMARK = {$\bullet$}, JOURNAL = {Scientific Reports}, VOLUME = {4}, PAGES = {1--9}, EID = {6837}, }
Endnote
%0 Journal Article %A Vu, Duong %A Szöke, Szániszló %A Wiwie, Christian %A Baumbach, Jan %A Cardinali, Gianluigi %A Röttger, Richard %A Robert, Vincent %+ external external Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society external external Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society external %T Massive Fungal Biodiversity Data Re-annotation with Multi-level Clustering : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-8F2B-2 %R 10.1038/srep06837 %7 2014-10-30 %D 2014 %8 30.10.2014 %J Scientific Reports %O Sci. Rep. %V 4 %& 1 %P 1 - 9 %Z sequence number: 6837 %I Nature Publishing Group %C London, UK
2013
130. Beggel B, Münk C, Däumer M, Hauck K, Häussinger D, Lengauer T, Ehrhardt A: Full Genome Ultra-deep Pyrosequencing Associates G-to-A-hypermutation of the Hepatitis B Virus Genome with the Natural Progression of Hepatitis B. Journal of Viral Hepatitis 2013, 20.
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@article{lengauer2013k, TITLE = {Full Genome Ultra-deep Pyrosequencing Associates {G-to-A-hypermutation} of the Hepatitis {B} Virus Genome with the Natural Progression of Hepatitis {B}}, AUTHOR = {Beggel, Bastian and M{\"u}nk, C. and D{\"a}umer, M. and Hauck, K. and H{\"a}ussinger, D. and Lengauer, Thomas and Ehrhardt, A.}, LANGUAGE = {eng}, ISSN = {1352-0504}, DOI = {10.1111/jvh.12110}, LOCALID = {Local-ID: E5B67F4DBA747F50C1257C0B00359108-lengauer2013k}, PUBLISHER = {Wiley-Blackwell}, ADDRESS = {Oxford}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, DATE = {2013}, JOURNAL = {Journal of Viral Hepatitis}, VOLUME = {20}, NUMBER = {12}, PAGES = {882--889}, }
Endnote
%0 Journal Article %A Beggel, Bastian %A Münk, C. %A Däumer, M. %A Hauck, K. %A Häussinger, D. %A Lengauer, Thomas %A Ehrhardt, A. %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T Full Genome Ultra-deep Pyrosequencing Associates G-to-A-hypermutation of the Hepatitis B Virus Genome with the Natural Progression of Hepatitis B : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0015-7C18-0 %R 10.1111/jvh.12110 %F OTHER: Local-ID: E5B67F4DBA747F50C1257C0B00359108-lengauer2013k %7 2013-06-07 %D 2013 %J Journal of Viral Hepatitis %V 20 %N 12 %& 882 %P 882 - 889 %I Wiley-Blackwell %C Oxford %@ false
131. Beggel B, Neumann-Fraune M, Kaiser R, Verheyen J, Lengauer T: Inferring Short-Range Linkage Information from Sequencing Chromatograms. PLoS One 2013, 8.
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@article{Beggel2013b, TITLE = {Inferring Short-Range Linkage Information from Sequencing Chromatograms}, AUTHOR = {Beggel, Bastian and Neumann-Fraune, Maria and Kaiser, Rolf and Verheyen, Jens and Lengauer, Thomas}, LANGUAGE = {eng}, ISSN = {1932-6203}, DOI = {10.1371/journal.pone.0081687}, LOCALID = {Local-ID: 87C1C5C13FE500FCC1257C61003E526A-Beggel2013b}, PUBLISHER = {Public Library of Science}, ADDRESS = {San Francisco, CA}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, JOURNAL = {PLoS One}, VOLUME = {8}, NUMBER = {12}, PAGES = {1--8}, EID = {e81687}, }
Endnote
%0 Journal Article %A Beggel, Bastian %A Neumann-Fraune, Maria %A Kaiser, Rolf %A Verheyen, Jens %A Lengauer, Thomas %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Inferring Short-Range Linkage Information from Sequencing Chromatograms : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0015-851F-E %R 10.1371/journal.pone.0081687 %F OTHER: Local-ID: 87C1C5C13FE500FCC1257C61003E526A-Beggel2013b %7 2013-12-20 %D 2013 %8 20.12.2013 %J PLoS One %V 8 %N 12 %& 1 %P 1 - 8 %Z sequence number: e81687 %I Public Library of Science %C San Francisco, CA %@ false
132. Bhadra T, Battacharya M, Feuerbach L, Lengauer T, Bandyopadhyay S: DNA Methylation Patterns Facilitate the Identification of MicroRNA Transcription Start Sites: A Brain-specific Study. PLoS One 2013, 8.
Abstract
Predicting the transcription start sites (TSSs) of microRNAs (miRNAs) is important for understanding how these small RNA molecules, known to regulate translation and stability of protein-coding genes, are regulated themselves. Previous approaches are primarily based on genetic features, trained on TSSs of protein-coding genes, and have low prediction accuracy. Recently, a support vector machine based technique has been proposed for miRNA TSS prediction that uses known miRNA TSS for training the classifier along with a set of existing and novel CpG island based features. Current progress in epigenetics research has provided genomewide and tissue-specific reports about various phenotypic traits. We hypothesize that incorporating epigenetic characteristics into statistical models may lead to better prediction of primary transcripts of human miRNAs. In this paper, we have tested our hypothesis on brain-specific miRNAs by using epigenetic as well as genetic features to predict the primary transcripts. For this, we have used a sophisticated feature selection technique and a robust classification model. Our prediction model achieves an accuracy of more than 80% and establishes the potential of epigenetic analysis for in silico prediction of TSSs.
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@article{lengauer2013j, TITLE = {{DNA} Methylation Patterns Facilitate the Identification of {microRNA} Transcription Start Sites: A Brain-specific Study}, AUTHOR = {Bhadra, Tapas and Battacharya, Malay and Feuerbach, Lars and Lengauer, Thomas and Bandyopadhyay, Sanghamitra}, LANGUAGE = {eng}, ISSN = {1932-6203}, URL = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3691241/?tool=pmcentrez&report=abstract}, DOI = {10.1371/journal.pone.0066722}, LOCALID = {Local-ID: 43F7490EA03DDC21C1257C0B00351960-lengauer2013j}, PUBLISHER = {Public Library of Science}, ADDRESS = {San Francisco, CA}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, ABSTRACT = {Predicting the transcription start sites (TSSs) of microRNAs (miRNAs) is important for understanding how these small RNA molecules, known to regulate translation and stability of protein-coding genes, are regulated themselves. Previous approaches are primarily based on genetic features, trained on TSSs of protein-coding genes, and have low prediction accuracy. Recently, a support vector machine based technique has been proposed for miRNA TSS prediction that uses known miRNA TSS for training the classifier along with a set of existing and novel CpG island based features. Current progress in epigenetics research has provided genomewide and tissue-specific reports about various phenotypic traits. We hypothesize that incorporating epigenetic characteristics into statistical models may lead to better prediction of primary transcripts of human miRNAs. In this paper, we have tested our hypothesis on brain-specific miRNAs by using epigenetic as well as genetic features to predict the primary transcripts. For this, we have used a sophisticated feature selection technique and a robust classification model. Our prediction model achieves an accuracy of more than 80% and establishes the potential of epigenetic analysis for in silico prediction of TSSs.}, JOURNAL = {PLoS One}, VOLUME = {8}, NUMBER = {6}, EID = {e66722}, }
Endnote
%0 Journal Article %A Bhadra, Tapas %A Battacharya, Malay %A Feuerbach, Lars %A Lengauer, Thomas %A Bandyopadhyay, Sanghamitra %+ External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T DNA Methylation Patterns Facilitate the Identification of MicroRNA Transcription Start Sites: A Brain-specific Study : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0015-7C0B-C %R 10.1371/journal.pone.0066722 %2 PMC3691241 %U http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3691241/?tool=pmcentrez&report=abstract %F OTHER: Local-ID: 43F7490EA03DDC21C1257C0B00351960-lengauer2013j %7 2013-06-24 %D 2013 %8 24.06.2013 %X Predicting the transcription start sites (TSSs) of microRNAs (miRNAs) is important for understanding how these small RNA molecules, known to regulate translation and stability of protein-coding genes, are regulated themselves. Previous approaches are primarily based on genetic features, trained on TSSs of protein-coding genes, and have low prediction accuracy. Recently, a support vector machine based technique has been proposed for miRNA TSS prediction that uses known miRNA TSS for training the classifier along with a set of existing and novel CpG island based features. Current progress in epigenetics research has provided genomewide and tissue-specific reports about various phenotypic traits. We hypothesize that incorporating epigenetic characteristics into statistical models may lead to better prediction of primary transcripts of human miRNAs. In this paper, we have tested our hypothesis on brain-specific miRNAs by using epigenetic as well as genetic features to predict the primary transcripts. For this, we have used a sophisticated feature selection technique and a robust classification model. Our prediction model achieves an accuracy of more than 80% and establishes the potential of epigenetic analysis for in silico prediction of TSSs. %J PLoS One %V 8 %N 6 %Z sequence number: e66722 %I Public Library of Science %C San Francisco, CA %@ false %U http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0066722
133. Bock C, Wutz A: DNA Methylation: A Matter of Culture. Nature Structural and Molecular Biology 2013, 20.
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@article{Bock2013bz, TITLE = {{DNA} Methylation: A Matter of Culture}, AUTHOR = {Bock, Christoph and Wutz, Anton}, LANGUAGE = {eng}, ISSN = {1545-9993}, DOI = {doi:10.1038/nsmb.2531}, PUBLISHER = {Nature Pub. Group}, ADDRESS = {New York, NY}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, JOURNAL = {Nature Structural and Molecular Biology}, VOLUME = {20}, PAGES = {249--251}, }
Endnote
%0 Journal Article %A Bock, Christoph %A Wutz, Anton %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T DNA Methylation: A Matter of Culture : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0018-A891-6 %R doi:10.1038/nsmb.2531 %7 2013-03-05 %D 2013 %8 05.03.2013 %J Nature Structural and Molecular Biology %O Nature Struct Biol %V 20 %& 249 %P 249 - 251 %I Nature Pub. Group %C New York, NY %@ false
134. Bozek K, Lengauer T, Sierra S, Kaiser R, Domingues FS: Analysis of Physicochemical and Structural Properties Determining HIV-1 Coreceptor Usage. PLoS Computational Biology 2013, 9.
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@article{lengauer2012g, TITLE = {Analysis of Physicochemical and Structural Properties Determining {HIV}-1 Coreceptor Usage}, AUTHOR = {Bozek, Katarzyna and Lengauer, Thomas and Sierra, Saleta and Kaiser, Rolf and Domingues, Francisco S.}, LANGUAGE = {eng}, ISSN = {1553-734X}, URL = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3605109&tool=pmcentrez&rendertype=abstract}, DOI = {10.1371/journal.pcbi.1002977}, LOCALID = {Local-ID: A15B25110B236E58C1257AD3004DB1C1-lengauer2012g}, PUBLISHER = {Public Library of Science}, ADDRESS = {San Francisco, CA}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, JOURNAL = {PLoS Computational Biology}, VOLUME = {9}, NUMBER = {3}, PAGES = {1--13}, EID = {e1002977}, }
Endnote
%0 Journal Article %A Bozek, Katarzyna %A Lengauer, Thomas %A Sierra, Saleta %A Kaiser, Rolf %A Domingues, Francisco S. %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations %T Analysis of Physicochemical and Structural Properties Determining HIV-1 Coreceptor Usage : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0015-7975-5 %2 3605109 %F OTHER: Local-ID: A15B25110B236E58C1257AD3004DB1C1-lengauer2012g %R 10.1371/journal.pcbi.1002977 %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3605109&tool=pmcentrez&rendertype=abstract %7 2013-03-21 %D 2013 %8 21.03.2013 %J PLoS Computational Biology %V 9 %N 3 %& 1 %P 1 - 13 %Z sequence number: e1002977 %I Public Library of Science %C San Francisco, CA %@ false
135. Cao K, Lailler N, Zhang Y, Kumar A, Uppal K, Liu Z, Lee EK, Wu H, Medrzycki M, Pan C, Ho P-Y, Cooper GP, Dong X, Bock C, Bouhassira EE, Fan Y: High-resolution Mapping of H1 Linker Histone Variants in Embryonic Stem Cells. PLoS Genetics 2013, 9.
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@article{Cao2013, TITLE = {High-Resolution Mapping of {H1} Linker Histone Variants in Embryonic Stem Cells}, AUTHOR = {Cao, Kaixiang and Lailler, Nathalie and Zhang, Yunzhe and Kumar, Ashwath and Uppal, Karan and Liu, Zheng and Lee, Eva K. and Wu, Hongwei and Medrzycki, Magdalena and Pan, Chenyi and Ho, Po-Yi and Cooper, Guy P. and Dong, Xiao and Bock, Christoph and Bouhassira, Eric E. and Fan, Yuhong}, LANGUAGE = {eng}, ISSN = {1553-7390; 1553-7404}, URL = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3636266&tool=pmcentrez&rendertype=abstract}, DOI = {10.1371/journal.pgen.1003417}, PUBLISHER = {Public Library of Science}, ADDRESS = {San Francisco, USA}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, DATE = {2013-04}, JOURNAL = {PLoS Genetics}, DEBUG = {author: Bock, Christoph}, VOLUME = {9}, NUMBER = {4}, EID = {e1003417}, }
Endnote
%0 Journal Article %A Cao, Kaixiang %A Lailler, Nathalie %A Zhang, Yunzhe %A Kumar, Ashwath %A Uppal, Karan %A Liu, Zheng %A Lee, Eva K. %A Wu, Hongwei %A Medrzycki, Magdalena %A Pan, Chenyi %A Ho, Po-Yi %A Cooper, Guy P. %A Dong, Xiao %A Bock, Christoph %A Bouhassira, Eric E. %A Fan, Yuhong %A contributor: Bickmore, Wendy A. %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations %T High-resolution Mapping of H1 Linker Histone Variants in Embryonic Stem Cells : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0018-AB5A-A %2 3636266 %F OTHER: publisher-idPGENETICS-D-12-00919 %R 10.1371/journal.pgen.1003417 %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3636266&tool=pmcentrez&rendertype=abstract %7 2013-04-25 %D 2013 %J PLoS Genetics %V 9 %N 4 %Z sequence number: e1003417 %I Public Library of Science %C San Francisco, USA %@ false
136. Dietz J, Schelhorn SE, Fitting D, Mihm U, Susser S, Welker M-W, Füller C, Däumer M, Teuber G, Wedemeyer H, Berg T, Lengauer T, Zeuzem S, Herrmann E, Sarrazin C: Deep Sequencing Reveals Mutagenic Effects of Ribavirin During Monotherapy of HCV Genotype 1-infected Patients. Journal of Virology 2013, 87.
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@article{lengauer2013h, TITLE = {Deep Sequencing Reveals Mutagenic Effects of Ribavirin During Monotherapy of {HCV} Genotype 1-infected Patients}, AUTHOR = {Dietz, Julia and Schelhorn, Sven Eric and Fitting, Daniel and Mihm, Ulrike and Susser, Simone and Welker, Martin-Walter and F{\"u}ller, Caterina and D{\"a}umer, Martin and Teuber, Gerlinde and Wedemeyer, Heiner and Berg, Thomas and Lengauer, Thomas and Zeuzem, Stefan and Herrmann, Eva and Sarrazin, Christoph}, LANGUAGE = {eng}, ISSN = {0022-538X}, DOI = {10.1128/JVI.02778-12}, LOCALID = {Local-ID: 14C01737FFEEBB1BC1257C0B0032E872-lengauer2013h}, PUBLISHER = {American Society for Microbiology}, ADDRESS = {Washington, DC}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, DATE = {2013}, JOURNAL = {Journal of Virology}, VOLUME = {87}, NUMBER = {11}, PAGES = {6172--6181}, }
Endnote
%0 Journal Article %A Dietz, Julia %A Schelhorn, Sven Eric %A Fitting, Daniel %A Mihm, Ulrike %A Susser, Simone %A Welker, Martin-Walter %A Füller, Caterina %A Däumer, Martin %A Teuber, Gerlinde %A Wedemeyer, Heiner %A Berg, Thomas %A Lengauer, Thomas %A Zeuzem, Stefan %A Herrmann, Eva %A Sarrazin, Christoph %+ External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations %T Deep Sequencing Reveals Mutagenic Effects of Ribavirin During Monotherapy of HCV Genotype 1-infected Patients : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0015-7C00-2 %2 PMC3648094 %R 10.1128/JVI.02778-12 %F OTHER: Local-ID: 14C01737FFEEBB1BC1257C0B0032E872-lengauer2013h %7 2013-03-27 %D 2013 %J Journal of Virology %V 87 %N 11 %& 6172 %P 6172 - 6181 %I American Society for Microbiology %C Washington, DC %@ false %U http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3648094/
137. Ellinghaus D, Zhang H, Zeissig S, Lipinski S, Till A, Jiang T, Stade B, Bromberg Y, Ellinghaus E, Keller A, Rivas MA, Skieceviciene J, Doncheva NT, Liu X, Liu Q, Jiang F, Forster M, Mayr G, Albrecht M, Häsler R, Boehm BO, Goodall J, Berzuini CR, Lee J, Andersen V, Vogel U, Kupcinskas L, Kayser M, Krawczak M, Nikolaus S, et al.: Association Between Variants of PRDM1 and NDP52 and Crohn’s Disease, Based on Exome Sequencing and Functional Studies. Gastroenterology 2013, 145.
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@article{Albrecht2013b, TITLE = {Association Between Variants of {PRDM1} and {NDP52} and {Crohn's} Disease, Based on Exome Sequencing and Functional Studies}, AUTHOR = {Ellinghaus, David and Zhang, Hu and Zeissig, Sebastian and Lipinski, Simone and Till, Andreas and Jiang, Tao and Stade, Bj{\"o}rn and Bromberg, Yana and Ellinghaus, Eva and Keller, Andreas and Rivas, Manuel A. and Skieceviciene, Jurgita and Doncheva, Nadezhda Tsankova and Liu, Xiao and Liu, Qing and Jiang, Fuman and Forster, Michael and Mayr, Gabriele and Albrecht, Mario and H{\"a}sler, Robert and Boehm, Bernhard O. and Goodall, Jane and Berzuini, Carlo R. and Lee, James and Andersen, Vibeke and Vogel, Ulla and Kupcinskas, Limas and Kayser, Manfred and Krawczak, Michael and Nikolaus, Susanna and Weersma, Rinse K. and Ponsioen, Cyriel Y. and Sans, Miquel and Wijmenga, Cisca and Strachan, David P. and McArdle, Wendy L. and Vermeire, S{\'e}verine and Rutgeerts, Paul and Sanderson, Jeremy D. and Mathew, Christopher G. and Vatn, Morten H. and Wang, Jun and N{\"o}then, Markus M. and Duerr, Richard H. and B{\"u}ning, Carsten and Brand, Stephan and Glas, J{\"u}rgen and Winkelmann, Juliane and Illig, Thomas and Latiano, Anna and Annese, Vito and Halfvarson, Jonas and D'Amato, Mauro and Daly, Mark J. and Nothnagel, Michael and Karlsen, Tom H. and Subramani, Suresh and Rosenstiel, Philip and Schreiber, Stefan and Parkes, Miles and Franke, Andre}, LANGUAGE = {eng}, ISSN = {0016-5085}, DOI = {10.1053/j.gastro.2013.04.040}, LOCALID = {Local-ID: D94481A97C347AB5C1257C70004CF69C-Albrecht2013b}, PUBLISHER = {W.B. Saunders}, ADDRESS = {Philadelphia, PA}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, DATE = {2013}, JOURNAL = {Gastroenterology}, VOLUME = {145}, NUMBER = {2}, PAGES = {339--347}, }
Endnote
%0 Journal Article %A Ellinghaus, David %A Zhang, Hu %A Zeissig, Sebastian %A Lipinski, Simone %A Till, Andreas %A Jiang, Tao %A Stade, Björn %A Bromberg, Yana %A Ellinghaus, Eva %A Keller, Andreas %A Rivas, Manuel A. %A Skieceviciene, Jurgita %A Doncheva, Nadezhda Tsankova %A Liu, Xiao %A Liu, Qing %A Jiang, Fuman %A Forster, Michael %A Mayr, Gabriele %A Albrecht, Mario %A Häsler, Robert %A Boehm, Bernhard O. %A Goodall, Jane %A Berzuini, Carlo R. %A Lee, James %A Andersen, Vibeke %A Vogel, Ulla %A Kupcinskas, Limas %A Kayser, Manfred %A Krawczak, Michael %A Nikolaus, Susanna %A Weersma, Rinse K. %A Ponsioen, Cyriel Y. %A Sans, Miquel %A Wijmenga, Cisca %A Strachan, David P. %A McArdle, Wendy L. %A Vermeire, Séverine %A Rutgeerts, Paul %A Sanderson, Jeremy D. %A Mathew, Christopher G. %A Vatn, Morten H. %A Wang, Jun %A Nöthen, Markus M. %A Duerr, Richard H. %A Büning, Carsten %A Brand, Stephan %A Glas, Jürgen %A Winkelmann, Juliane %A Illig, Thomas %A Latiano, Anna %A Annese, Vito %A Halfvarson, Jonas %A D'Amato, Mauro %A Daly, Mark J. %A Nothnagel, Michael %A Karlsen, Tom H. %A Subramani, Suresh %A Rosenstiel, Philip %A Schreiber, Stefan %A Parkes, Miles %A Franke, Andre %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations %T Association Between Variants of PRDM1 and NDP52 and Crohn's Disease, Based on Exome Sequencing and Functional Studies : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0015-79A5-A %R 10.1053/j.gastro.2013.04.040 %2 PMC3753067 %F OTHER: Local-ID: D94481A97C347AB5C1257C70004CF69C-Albrecht2013b %7 2013-04-25 %D 2013 %J Gastroenterology %O Gastroenterology %V 145 %N 2 %& 339 %P 339 - 347 %I W.B. Saunders %C Philadelphia, PA %@ false
138. Hauschild A-C, Kopczynski D, D’Addario M, Baumbach JI, Rahmann S, Baumbach J: Peak Detection Method Evaluation for Ion Mobility Spectrometry by using Machine Learning Approaches. Metabolites 2013, 3.
Abstract
Ion mobility spectrometry with pre-separation by multi-capillary columns (MCC/IMS) has become an established inexpensive, non-invasive bioanalytics technology for detecting volatile organic compounds (VOCs) with various metabolomics applications in medical research. To pave the way for this technology towards daily usage in medical practice, different steps still have to be taken. With respect to modern biomarker research, one of the most important tasks is the automatic classification of patient-specific data sets into different groups, healthy or not, for instance. Although sophisticated machine learning methods exist, an inevitable preprocessing step is reliable and robust peak detection without manual intervention. In this work we evaluate four state-of-the-art approaches for automated IMS-based peak detection: local maxima search, watershed transformation with IPHEx, region-merging with VisualNow, and peak model estimation (PME).We manually generated Metabolites 2013, 3 278 a gold standard with the aid of a domain expert (manual) and compare the performance of the four peak calling methods with respect to two distinct criteria. We first utilize established machine learning methods and systematically study their classification performance based on the four peak detectors� results. Second, we investigate the classification variance and robustness regarding perturbation and overfitting. Our main finding is that the power of the classification accuracy is almost equally good for all methods, the manually created gold standard as well as the four automatic peak finding methods. In addition, we note that all tools, manual and automatic, are similarly robust against perturbations. However, the classification performance is more robust against overfitting when using the PME as peak calling preprocessor. In summary, we conclude that all methods, though small differences exist, are largely reliable and enable a wide spectrum of real-world biomedical applications.
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@article{Hauschild2012c, TITLE = {Peak Detection Method Evaluation for Ion Mobility Spectrometry by using Machine Learning Approaches}, AUTHOR = {Hauschild, Anne-Christin and Kopczynski, Dominik and D'Addario, Marianna and Baumbach, J{\"o}rg Ingo and Rahmann, Sven and Baumbach, Jan}, LANGUAGE = {eng}, ISSN = {2218-1989}, DOI = {10.3390/metabo3020277}, LOCALID = {Local-ID: 13BE6437764CE4D3C1257C660052EF3B-Hauschild2012c}, PUBLISHER = {MDPI}, ADDRESS = {Basel}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, ABSTRACT = {Ion mobility spectrometry with pre-separation by multi-capillary columns (MCC/IMS) has become an established inexpensive, non-invasive bioanalytics technology for detecting volatile organic compounds (VOCs) with various metabolomics applications in medical research. To pave the way for this technology towards daily usage in medical practice, different steps still have to be taken. With respect to modern biomarker research, one of the most important tasks is the automatic classification of patient-specific data sets into different groups, healthy or not, for instance. Although sophisticated machine learning methods exist, an inevitable preprocessing step is reliable and robust peak detection without manual intervention. In this work we evaluate four state-of-the-art approaches for automated IMS-based peak detection: local maxima search, watershed transformation with IPHEx, region-merging with VisualNow, and peak model estimation (PME).We manually generated Metabolites 2013, 3 278 a gold standard with the aid of a domain expert (manual) and compare the performance of the four peak calling methods with respect to two distinct criteria. We first utilize established machine learning methods and systematically study their classification performance based on the four peak detectors{\diamond} results. Second, we investigate the classification variance and robustness regarding perturbation and overfitting. Our main finding is that the power of the classification accuracy is almost equally good for all methods, the manually created gold standard as well as the four automatic peak finding methods. In addition, we note that all tools, manual and automatic, are similarly robust against perturbations. However, the classification performance is more robust against overfitting when using the PME as peak calling preprocessor. In summary, we conclude that all methods, though small differences exist, are largely reliable and enable a wide spectrum of real-world biomedical applications.}, JOURNAL = {Metabolites}, VOLUME = {3}, NUMBER = {2}, PAGES = {277--293}, }
Endnote
%0 Journal Article %A Hauschild, Anne-Christin %A Kopczynski, Dominik %A D'Addario, Marianna %A Baumbach, Jörg Ingo %A Rahmann, Sven %A Baumbach, Jan %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Peak Detection Method Evaluation for Ion Mobility Spectrometry by using Machine Learning Approaches : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0015-84FC-4 %R 10.3390/metabo3020277 %F OTHER: Local-ID: 13BE6437764CE4D3C1257C660052EF3B-Hauschild2012c %7 2013-04-16 %D 2013 %8 16.04.2013 %X Ion mobility spectrometry with pre-separation by multi-capillary columns (MCC/IMS) has become an established inexpensive, non-invasive bioanalytics technology for detecting volatile organic compounds (VOCs) with various metabolomics applications in medical research. To pave the way for this technology towards daily usage in medical practice, different steps still have to be taken. With respect to modern biomarker research, one of the most important tasks is the automatic classification of patient-specific data sets into different groups, healthy or not, for instance. Although sophisticated machine learning methods exist, an inevitable preprocessing step is reliable and robust peak detection without manual intervention. In this work we evaluate four state-of-the-art approaches for automated IMS-based peak detection: local maxima search, watershed transformation with IPHEx, region-merging with VisualNow, and peak model estimation (PME).We manually generated Metabolites 2013, 3 278 a gold standard with the aid of a domain expert (manual) and compare the performance of the four peak calling methods with respect to two distinct criteria. We first utilize established machine learning methods and systematically study their classification performance based on the four peak detectors� results. Second, we investigate the classification variance and robustness regarding perturbation and overfitting. Our main finding is that the power of the classification accuracy is almost equally good for all methods, the manually created gold standard as well as the four automatic peak finding methods. In addition, we note that all tools, manual and automatic, are similarly robust against perturbations. However, the classification performance is more robust against overfitting when using the PME as peak calling preprocessor. In summary, we conclude that all methods, though small differences exist, are largely reliable and enable a wide spectrum of real-world biomedical applications. %J Metabolites %V 3 %N 2 %& 277 %P 277 - 293 %I MDPI %C Basel %@ false %U http://dx.doi.org/10.3390/metabo3020277
139. Hauschild A-C, Baumbach JI, Baumbach J: Paving the Way for Automated Clinical Breath Analysis and Biomarker Detection. In GCB 2013 Göttingen - Highlight Papers. GCB; 2013.
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@inproceedings{Hauschild2013b, TITLE = {Paving the Way for Automated Clinical Breath Analysis and Biomarker Detection}, AUTHOR = {Hauschild, Anne-Christin and Baumbach, Joerg Ingo and Baumbach, Jan}, LANGUAGE = {eng}, PUBLISHER = {GCB}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, BOOKTITLE = {GCB 2013 G{\"o}ttingen -- Highlight Papers}, PAGES = {24--28}, ADDRESS = {G{\"o}ttingen, Germany}, }
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%0 Conference Proceedings %A Hauschild, Anne-Christin %A Baumbach, Joerg Ingo %A Baumbach, Jan %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Paving the Way for Automated Clinical Breath Analysis and Biomarker Detection : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0015-84EA-C %D 2013 %B GCB 2013 %Z date of event: 2013-09-10 - 2013-09-13 %C Göttingen, Germany %B GCB 2013 Göttingen - Highlight Papers %P 24 - 28 %I GCB %U http://www.gcb2013.de/system/resources/BAhbBlsHOgZmSSIxMjAxMy8wOS8xMC8yM180NF81OF8xNDVfZ2NiMTNfaGlnaGxpZ2h0cy5wZGYGOgZFVA/gcb13_highlights.pdf
140. Jungwirth B, Sala C, Kohl TA, Uplekar S, Baumbach J, Cole S, Pühler A, Tauch A: High-r esolution Detection of DNA Binding Sites of the Global Transcriptional Regulator GlxR in Corynebacterium Glutamicum. Microbiology 2013, 159.
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@article{Baumbach2013b, TITLE = {High-resolution detection of {DNA} binding sites of the global transcriptional regulator {GlxR} in {Corynebacterium} glutamicum}, AUTHOR = {Jungwirth, Britta and Sala, Claudia and Kohl, Thomas A. and Uplekar, Swapna and Baumbach, Jan and Cole, Steward and P{\"u}hler, Alfred and Tauch, Andreas}, LANGUAGE = {eng}, ISSN = {1350-0872}, DOI = {10.1099/mic.0.062059-0}, PUBLISHER = {Society for General Microbiology}, ADDRESS = {Reading}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, DATE = {2013}, JOURNAL = {Microbiology}, VOLUME = {159}, NUMBER = {1}, PAGES = {12--22}, }
Endnote
%0 Journal Article %A Jungwirth, Britta %A Sala, Claudia %A Kohl, Thomas A. %A Uplekar, Swapna %A Baumbach, Jan %A Cole, Steward %A Pühler, Alfred %A Tauch, Andreas %+ External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations %T High-r esolution Detection of DNA Binding Sites of the Global Transcriptional Regulator GlxR in Corynebacterium Glutamicum : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0018-A757-1 %R 10.1099/mic.0.062059-0 %7 2012-10-25 %D 2013 %J Microbiology %V 159 %N 1 %& 12 %P 12 - 22 %I Society for General Microbiology %C Reading %@ false
141. Kacprowski T, Doncheva NT, Albrecht M: NetworkPrioritizer: a Versatile Tool for Network-based Prioritization of Candidate Disease Genes or Other Molecules. Bioinformatics 2013, 29.
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@article{Albrecht2013d, TITLE = {{NetworkPrioritizer}: {A} Versatile Tool for Network-based Prioritization of Candidate Disease Genes or Other Molecules}, AUTHOR = {Kacprowski, Tim and Doncheva, Nadezhda Tsankova and Albrecht, Mario}, LANGUAGE = {eng}, ISSN = {1367-4803}, DOI = {10.1093/bioinformatics/btt164}, LOCALID = {Local-ID: 01CE323C97D6DDB6C1257C60005071DC-Albrecht2013d}, PUBLISHER = {Oxford University Press}, ADDRESS = {Oxford, UK}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, DATE = {2013}, JOURNAL = {Bioinformatics}, VOLUME = {29}, NUMBER = {11}, PAGES = {1471--1473}, }
Endnote
%0 Journal Article %A Kacprowski, Tim %A Doncheva, Nadezhda Tsankova %A Albrecht, Mario %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T NetworkPrioritizer: a Versatile Tool for Network-based Prioritization of Candidate Disease Genes or Other Molecules : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0015-8146-3 %R 10.1093/bioinformatics/btt164 %2 PMC3661055 %F OTHER: Local-ID: 01CE323C97D6DDB6C1257C60005071DC-Albrecht2013d %7 2013-04-16 %D 2013 %J Bioinformatics %V 29 %N 11 %& 1471 %P 1471 - 1473 %I Oxford University Press %C Oxford, UK %@ false %U http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3661055/
142. Kalaghatgi P, Lawyer G: Inter-country Mixing in HIV Transmission Clusters: a Pan-European Phylodynamics Study. In Reviews in Antiviral Therapy & Infectious Diseases. Virology Education; 2013.
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@inproceedings{Kalaghatgi2013, TITLE = {Inter-country Mixing in {HIV} Transmission Clusters: {A} {pan-European} Phylodynamics Study}, AUTHOR = {Kalaghatgi, Prabhav and Lawyer, Glenn}, LANGUAGE = {eng}, LOCALID = {Local-ID: 893733FC0B2A8D2DC1257C82004F1600-Kalaghatgi2013}, PUBLISHER = {Virology Education}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, DATE = {2013}, BOOKTITLE = {Abstract Book 11th European Workshop on HIV \& Hepatitis Treatment Strategies \& Antiviral Drug Resistance}, PAGES = {9--9}, EID = {O-07}, JOURNAL = {Reviews in Antiviral Therapy \& Infectious Diseases}, VOLUME = {13-2}, ADDRESS = {Rome, Italy}, }
Endnote
%0 Conference Proceedings %A Kalaghatgi, Prabhav %A Lawyer, Glenn %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Inter-country Mixing in HIV Transmission Clusters: a Pan-European Phylodynamics Study : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0015-8127-7 %F OTHER: Local-ID: 893733FC0B2A8D2DC1257C82004F1600-Kalaghatgi2013 %D 2013 %B 11th European Workshop on HIV & Hepatitis %Z date of event: 2013-03-20 - 2013-03-22 %C Rome, Italy %B Abstract Book 11th European Workshop on HIV & Hepatitis Treatment Strategies & Antiviral Drug Resistance %P 9 - 9 %Z sequence number: O-07 %I Virology Education %J Reviews in Antiviral Therapy & Infectious Diseases %V 13-2 %U http://regist2.virology-education.com/abstractbook/2013_2.pdfhttp://regist2.virology-education.com/2013/11EU/docs/09_Kalaghatgi.pdf
143. Kalinina OV, Pfeifer N, Lengauer T: Modelling Binding Between CCR5 and CXCR4 Receptors and Their Ligands Suggests the Surface Electrostatic Potential of the Co-receptor to Be a Key Player in the HIV-1 Tropism. Retrovirology 2013, 10.
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@article{Kalinina2013, TITLE = {Modelling Binding Between {CCR5} and {CXCR4} Receptors and Their Ligands Suggests the Surface Electrostatic Potential of the Co-receptor to Be a Key Player in the {HIV}-1 Tropism}, AUTHOR = {Kalinina, Olga V. and Pfeifer, Nico and Lengauer, Thomas}, LANGUAGE = {eng}, ISSN = {1742-4690}, URL = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3833284&tool=pmcentrez&rendertype=abstract}, DOI = {10.1186/1742-4690-10-130}, LOCALID = {Local-ID: 9D600A85819064AEC1257C6A00543F15-Kalinina2013}, PUBLISHER = {BioMed Central}, ADDRESS = {London}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, JOURNAL = {Retrovirology}, VOLUME = {10}, PAGES = {130:1--130:11}, EID = {130}, }
Endnote
%0 Journal Article %A Kalinina, Olga V. %A Pfeifer, Nico %A Lengauer, Thomas %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Modelling Binding Between CCR5 and CXCR4 Receptors and Their Ligands Suggests the Surface Electrostatic Potential of the Co-receptor to Be a Key Player in the HIV-1 Tropism : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0015-7963-B %2 3833284 %F OTHER: Local-ID: 9D600A85819064AEC1257C6A00543F15-Kalinina2013 %R 10.1186/1742-4690-10-130 %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3833284&tool=pmcentrez&rendertype=abstract %7 2013-11-11 %D 2013 %8 11.11.2013 %K Tropism test %J Retrovirology %V 10 %& 130:1 %P 130:1 - 130:11 %Z sequence number: 130 %I BioMed Central %C London %@ false
144. Lengauer T, Nussinov R: New Methods Section in PLOS Computational Biology. PLoS Computational Biology 2013, 9.
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@article{LengauerNussinov2013, TITLE = {New Methods Section in {PLOS} Computational Biology}, AUTHOR = {Lengauer, Thomas and Nussinov, Ruth}, LANGUAGE = {eng}, ISSN = {1553-734X; 1553-7358}, URL = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3591281&tool=pmcentrez&rendertype=abstract}, DOI = {10.1371/journal.pcbi.1002972}, PUBLISHER = {Public Library of Science}, ADDRESS = {San Francisco, USA}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, DATE = {2013}, JOURNAL = {PLoS Computational Biology}, VOLUME = {9}, NUMBER = {3}, EID = {e1002972}, }
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%0 Journal Article %A Lengauer, Thomas %A Nussinov, Ruth %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T New Methods Section in PLOS Computational Biology : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0027-AA4F-0 %2 3591281 %F OTHER: publisher-idPCOMPBIOL-D-13-00169 %R 10.1371/journal.pcbi.1002972 %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3591281&tool=pmcentrez&rendertype=abstract %7 2013-03-07 %D 2013 %J PLoS Computational Biology %V 9 %N 3 %Z sequence number: e1002972 %I Public Library of Science %C San Francisco, USA %@ false
145. Lengauer T: Stellenwert der Bioinformatik für die personalisierte Medizin. Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz 2013, 56.
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@article{Langauer2013a, TITLE = {{Stellenwert der {Bioinformatik} f\"ur die personalisierte {Medizin}}}, AUTHOR = {Lengauer, Thomas}, LANGUAGE = {deu}, ISSN = {1436-9990}, DOI = {10.1007/s00103-013-1819-x}, PUBLISHER = {Springer}, ADDRESS = {Berlin}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, DATE = {2013}, JOURNAL = {Bundesgesundheitsblatt -- Gesundheitsforschung -- Gesundheitsschutz}, VOLUME = {56}, NUMBER = {11}, PAGES = {1489--1494}, }
Endnote
%0 Journal Article %A Lengauer, Thomas %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Stellenwert der Bioinformatik für die personalisierte Medizin : %G deu %U http://hdl.handle.net/11858/00-001M-0000-0018-AAC2-6 %R 10.1007/s00103-013-1819-x %7 2013 %D 2013 %J Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz %V 56 %N 11 %& 1489 %P 1489 - 1494 %I Springer %C Berlin %@ false
146. Liu JZ, Hov JR, Folseraas T, Ellinghaus E, Rushbrook SM, Doncheva NT, Andreassen OA, Weersma RK, Weismuller TJ, Eksteen B, Invernizzi P, Hirschfield GM, Gotthardt DN, Pares A, Ellinghaus D, Shah T, Juran BD, Milkiewicz P, Rust C, Schramm C, Müller T, Srivastava B, Dalekos G, Nöthen MM, Herms S, Winkelmann J, Mitrovic M, Braun F, Ponsioen CY, Croucher PJP, et al.: Dense Genotyping of Immune-related Disease Regions Identifies Nine New Risk Loci for Primary Sclerosing Cholangitis. Nature Genetics 2013, 45.
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@article{Albrecht2013a, TITLE = {Dense Genotyping of Immune-related Disease Regions Identifies Nine New Risk Loci for Primary Sclerosing Cholangitis}, AUTHOR = {Liu, Jimmy Z. and Hov, Johannes Roksund and Folseraas, Trine and Ellinghaus, Eva and Rushbrook, Simon M. and Doncheva, Nadezhda Tsankova and Andreassen, Ole A. and Weersma, Rinse K. and Weismuller, Tobias J. and Eksteen, Bertus and Invernizzi, Pietro and Hirschfield, Gideon M. and Gotthardt, Daniel Nils and Pares, Albert and Ellinghaus, David and Shah, Tejas and Juran, Brian D. and Milkiewicz, Piotr and Rust, Christian and Schramm, Christoph and M{\"u}ller, Tobias and Srivastava, Brijesh and Dalekos, Georgios and N{\"o}then, Markus M. and Herms, Stefan and Winkelmann, Juliane and Mitrovic, Mitja and Braun, Felix and Ponsioen, Cyriel Y. and Croucher, Peter J. P. and Sterneck, Martina and Teufel, Andreas and Mason, Andrew L. and Saarela, Janna and Leppa, Virpi and Dorfman, Ruslan and Alvaro, Domenico and Floreani, Annarosa and Onengut-Gumuscu, Suna and Rich, Stephen S. and Thompson, Wesley K. and Schork, Andrew J. and Naess, Sigrid and Thomsen, Ingo and Mayr, Gabriele and K{\"o}nig, Inke R. and Hveem, Kristian and Cleynen, Isabelle and Gutierrez-Achury, Javier and Rica{\~n}o-Ponce, Isis and van Heel, David and Bj{\"o}rnsson, Einar and Sandford, Richard N. and Durie, Peter R. and Melum, Espen and Vatn, Morten H. and Silverberg, Mark S. and Duerr, Richard H. and Padyukov, Leonid and Brand, Stephan and Sans, Miquel and Annese, Vito and Achkar, Jean-Paul and Boberg, Kirsten Muri and Marschall, Hanns-Ulrich and Chazouill{\`e}res, Olivier and Bowlus, Christopher L. and Wijmenga, Cisca and Schrumpf, Erik and Vermeire, Severine and Albrecht, Mario and Rioux, John D. and Alexander, Graeme and Bergquist, Annika and Cho, Judy and Schreiber, Stefan and Manns, Michael P. and F{\"a}rkkil{\"a}, Martti and Dale, Anders M. and Chapman, Roger W. and Lazaridis, Konstantinos N. and Franke, Andre and Anderson, Carl A. and Karlsen, Tom H.}, LANGUAGE = {eng}, ISSN = {1061-4036}, DOI = {10.1038/ng.2616}, LOCALID = {Local-ID: 10209969026DD7EDC1257C70004C724B-Albrecht2013a}, PUBLISHER = {Nature Publ. Group}, ADDRESS = {New York, NY}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, DATE = {2013}, JOURNAL = {Nature Genetics}, VOLUME = {45}, NUMBER = {6}, PAGES = {670--677}, }
Endnote
%0 Journal Article %A Liu, Jimmy Z. %A Hov, Johannes Roksund %A Folseraas, Trine %A Ellinghaus, Eva %A Rushbrook, Simon M. %A Doncheva, Nadezhda Tsankova %A Andreassen, Ole A. %A Weersma, Rinse K. %A Weismuller, Tobias J. %A Eksteen, Bertus %A Invernizzi, Pietro %A Hirschfield, Gideon M. %A Gotthardt, Daniel Nils %A Pares, Albert %A Ellinghaus, David %A Shah, Tejas %A Juran, Brian D. %A Milkiewicz, Piotr %A Rust, Christian %A Schramm, Christoph %A Müller, Tobias %A Srivastava, Brijesh %A Dalekos, Georgios %A Nöthen, Markus M. %A Herms, Stefan %A Winkelmann, Juliane %A Mitrovic, Mitja %A Braun, Felix %A Ponsioen, Cyriel Y. %A Croucher, Peter J. P. %A Sterneck, Martina %A Teufel, Andreas %A Mason, Andrew L. %A Saarela, Janna %A Leppa, Virpi %A Dorfman, Ruslan %A Alvaro, Domenico %A Floreani, Annarosa %A Onengut-Gumuscu, Suna %A Rich, Stephen S. %A Thompson, Wesley K. %A Schork, Andrew J. %A Naess, Sigrid %A Thomsen, Ingo %A Mayr, Gabriele %A König, Inke R. %A Hveem, Kristian %A Cleynen, Isabelle %A Gutierrez-Achury, Javier %A Ricaño-Ponce, Isis %A van Heel, David %A Björnsson, Einar %A Sandford, Richard N. %A Durie, Peter R. %A Melum, Espen %A Vatn, Morten H. %A Silverberg, Mark S. %A Duerr, Richard H. %A Padyukov, Leonid %A Brand, Stephan %A Sans, Miquel %A Annese, Vito %A Achkar, Jean-Paul %A Boberg, Kirsten Muri %A Marschall, Hanns-Ulrich %A Chazouillères, Olivier %A Bowlus, Christopher L. %A Wijmenga, Cisca %A Schrumpf, Erik %A Vermeire, Severine %A Albrecht, Mario %A Rioux, John D. %A Alexander, Graeme %A Bergquist, Annika %A Cho, Judy %A Schreiber, Stefan %A Manns, Michael P. %A Färkkilä, Martti %A Dale, Anders M. %A Chapman, Roger W. %A Lazaridis, Konstantinos N. %A Franke, Andre %A Anderson, Carl A. %A Karlsen, Tom H. %+ External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations %T Dense Genotyping of Immune-related Disease Regions Identifies Nine New Risk Loci for Primary Sclerosing Cholangitis : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0015-7A0A-D %R 10.1038/ng.2616 %2 PMC3667736 %F OTHER: Local-ID: 10209969026DD7EDC1257C70004C724B-Albrecht2013a %7 2013-04-21 %D 2013 %J Nature Genetics %O Nature Genet. %V 45 %N 6 %& 670 %P 670 - 677 %I Nature Publ. Group %C New York, NY %@ false %U http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3667736/
147. Michels KB, Binder AM, Dedeurwaerder S, Epstein CB, Greally JM, Gut I, Houseman EA, Bock C, Irizarry RA: Recommendations for the Design and Analysis of Epigenome-wide Association Studies. Nature Methods 2013, 10.
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@article{Bock2013b, TITLE = {Recommendations for the Design and Analysis of Epigenome-wide Association Studies}, AUTHOR = {Michels, Karin B. and Binder, Alexandra M. and Dedeurwaerder, Sarah and Epstein, Charles B. and Greally, John M. and Gut, Ivo and Houseman, E. Andres and Bock, Christoph and Irizarry, Rafael A.}, LANGUAGE = {eng}, ISSN = {1548-7091}, DOI = {doi:10.1038/nmeth.2632}, PUBLISHER = {Nature Pub. Group}, ADDRESS = {New York, NY}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, JOURNAL = {Nature Methods}, VOLUME = {10}, PAGES = {949--955}, }
Endnote
%0 Journal Article %A Michels, Karin B. %A Binder, Alexandra M. %A Dedeurwaerder, Sarah %A Epstein, Charles B. %A Greally, John M. %A Gut, Ivo %A Houseman, E. Andres %A Bock, Christoph %A Irizarry, Rafael A. %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T Recommendations for the Design and Analysis of Epigenome-wide Association Studies : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0018-AAA1-0 %R doi:10.1038/nmeth.2632 %7 2013-09-27 %D 2013 %8 27.09.2013 %J Nature Methods %V 10 %& 949 %P 949 - 955 %I Nature Pub. Group %C New York, NY %@ false
148. Oette M, Reuter S, Kaier R, Jensen B, Lengauer T, Fatkenheuer G, Knechten H, Hower M, Sagir A, Pfister H, Haussinger D: Ambulatory Care for HIV-infected Patients: Differences in Outcomes between Hospital-based Units and Private Practices: Analysis of the RESINA Cohort. European Journal of Medical Research 2013, 18.
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@article{Lengauer2013, TITLE = {Ambulatory care for {HIV}-infected patients: differences in outcomes between hospital-based units and private practices: analysis of the {RESINA} cohort}, AUTHOR = {Oette, Mark and Reuter, Stefan and Kaier, Rolf and Jensen, Bjoern and Lengauer, Thomas and Fatkenheuer, Gerd and Knechten, Heribert and Hower, Martin and Sagir, Abdurrahman and Pfister, Herbert and Haussinger, Dieter}, LANGUAGE = {eng}, DOI = {10.1186/2047-783X-18-48}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, JOURNAL = {European Journal of Medical Research}, VOLUME = {18}, EID = {48}, }
Endnote
%0 Journal Article %A Oette, Mark %A Reuter, Stefan %A Kaier, Rolf %A Jensen, Bjoern %A Lengauer, Thomas %A Fatkenheuer, Gerd %A Knechten, Heribert %A Hower, Martin %A Sagir, Abdurrahman %A Pfister, Herbert %A Haussinger, Dieter %+ External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations %T Ambulatory Care for HIV-infected Patients: Differences in Outcomes between Hospital-based Units and Private Practices: Analysis of the RESINA Cohort : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0018-AAD3-F %R 10.1186/2047-783X-18-48 %7 2013-11-21 %D 2013 %8 21.11.2013 %J European Journal of Medical Research %V 18 %Z sequence number: 48
149. Patil KR: Genome Signature based Sequence Comparison for Taxonomic Assignment and Tree Inference. Universität des Saarlandes; 2013.
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@phdthesis{Patil2013, TITLE = {Genome Signature based Sequence Comparison for Taxonomic Assignment and Tree Inference}, AUTHOR = {Patil, Kaustubh Raosaheb}, LANGUAGE = {eng}, URL = {urn:nbn:de:bsz:291-scidok-52973}, LOCALID = {Local-ID: 58D1B1989200E496C1257BFF002517BF-Patil2013}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, DATE = {2013-01}, }
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%0 Thesis %A Patil, Kaustubh Raosaheb %Y Lengauer, Thomas %A referee: McHardy, Alice Carolyn %+ Computational Genomics and Epidemiology, MPI for Informatics, Max Planck Society International Max Planck Research School, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Genomics and Epidemiology, MPI for Informatics, Max Planck Society %T Genome Signature based Sequence Comparison for Taxonomic Assignment and Tree Inference : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0015-7BB7-0 %U urn:nbn:de:bsz:291-scidok-52973 %F OTHER: Local-ID: 58D1B1989200E496C1257BFF002517BF-Patil2013 %I Universität des Saarlandes %C Saarbrücken %D 2013 %V phd %9 phd %U http://scidok.sulb.uni-saarland.de/volltexte/2013/5297/http://scidok.sulb.uni-saarland.de/doku/lic_ohne_pod.php?la=de
150. Pfeifer N, Lengauer T: Association Between HIV-1 Coreceptor Usage and Resistance to Some Broadly Neutralizing Antibodies. AIDS Research and Human Retroviruses (Proc AIDS Vaccine Conference 2013) 2013, 29.
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@article{PfeiferLengauer2013, TITLE = {Association Between {HIV-1} Coreceptor Usage and Resistance to Some Broadly Neutralizing Antibodies}, AUTHOR = {Pfeifer, Nico and Lengauer, Thomas}, ISSN = {0889-2229}, DOI = {:10.1089/aid.2013.1500}, LOCALID = {Local-ID: EEE62E1144F8CC8BC1257C6A0055F9A3-PfeiferLengauer2013}, PUBLISHER = {Mary Ann Liebert, Inc.}, ADDRESS = {Larchmont, NY}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, DATE = {2013}, JOURNAL = {AIDS Research and Human Retroviruses (Proc. AIDS Vaccine Conference)}, VOLUME = {29}, NUMBER = {11}, PAGES = {A60--A60}, EID = {P03.55}, BOOKTITLE = {AIDS Vaccine Conference 2013}, }
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%0 Journal Article %A Pfeifer, Nico %A Lengauer, Thomas %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Association Between HIV-1 Coreceptor Usage and Resistance to Some Broadly Neutralizing Antibodies : %U http://hdl.handle.net/11858/00-001M-0000-0015-842D-5 %R :10.1089/aid.2013.1500 %F OTHER: Local-ID: EEE62E1144F8CC8BC1257C6A0055F9A3-PfeiferLengauer2013 %7 2013-10-10 %D 2013 %J AIDS Research and Human Retroviruses %O Aids Res. Hum. Retrovir. %V 29 %N 11 %& A60 %P A60 - A60 %Z sequence number: P03.55 %I Mary Ann Liebert, Inc. %C Larchmont, NY %@ false %B AIDS Vaccine Conference 2013 %O AIDS Vaccine Conference 2013 Barcelona, Spain, 7 - 10 October 2013
151. Pironti A, Sierra S, Kaiser R, Lengauer T, Pfeifer N: In Silico Analysis of the Effects of Sequencing Errors on Geno2pheno[Coreceptor]. In Antiviral Therapy. International Medical Press; 2013(Supplement 1).
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@inproceedings{Pironti2013, TITLE = {In Silico Analysis of the Effects of Sequencing Errors on Geno2pheno[Coreceptor]}, AUTHOR = {Pironti, Alejandro and Sierra, Saleta and Kaiser, Rolf and Lengauer, Thomas and Pfeifer, Nico}, LANGUAGE = {eng}, ISSN = {1359-6535}, LOCALID = {Local-ID: C79B1849D90C0A33C1257C6A004EA3D3-Pironti2013}, PUBLISHER = {International Medical Press}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, BOOKTITLE = {Abstracts presented at the International Workshop on HIV \& Hepatitis Virus Drug Resistance and Curative Strategies}, ISSUE = {Supplement 1}, PAGES = {111--111}, EID = {A142}, JOURNAL = {Antiviral Therapy}, VOLUME = {18}, ISSUE = {Suppl. 1}, ADDRESS = {Toronto, Canada}, }
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%0 Conference Proceedings %A Pironti, Alejandro %A Sierra, Saleta %A Kaiser, Rolf %A Lengauer, Thomas %A Pfeifer, Nico %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T In Silico Analysis of the Effects of Sequencing Errors on Geno2pheno[Coreceptor] : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0015-7B4C-4 %F OTHER: Local-ID: C79B1849D90C0A33C1257C6A004EA3D3-Pironti2013 %D 2013 %B International Workshop on HIV & Hepatitis Virus Drug Resistance and Curative Strategies %Z date of event: 2013-06-04 - 2013-06-08 %C Toronto, Canada %B Abstracts presented at the International Workshop on HIV & Hepatitis Virus Drug Resistance and Curative Strategies %N Supplement 1 %P 111 - 111 %Z sequence number: A142 %I International Medical Press %J Antiviral Therapy %V 18 %N Suppl. 1 %@ false
152. Pironti A, Sierra S, Kaiser R, Lengauer T, Pfeifer N: Effects of Sequencing Errors on Geno2pheno[Coreceptor] Predictions. In Reviews in Antiviral Therapy & Infectious Diseases. Virology Education; 2013.
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@inproceedings{Pironti2013z, TITLE = {Effects of Sequencing Errors on Geno2pheno[Coreceptor] Predictions}, AUTHOR = {Pironti, Alejandro and Sierra, Saleta and Kaiser, Rolf and Lengauer, Thomas and Pfeifer, Nico}, LANGUAGE = {eng}, LOCALID = {Local-ID: E65A7D34540A5DBAC1257C6A004EF397-Pironti2013z}, PUBLISHER = {Virology Education}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, BOOKTITLE = {Abstract Book 11th European Meeting on HIV \& Hepatitis Treatment Strategies \& Antiviral Drug Resistance}, PAGES = {23--24}, EID = {Abstract O{\textunderscore}21}, JOURNAL = {Reviews in Antiviral Therapy \& Infectious Diseases}, VOLUME = {13-2}, ADDRESS = {Rome, Italy}, }
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%0 Conference Proceedings %A Pironti, Alejandro %A Sierra, Saleta %A Kaiser, Rolf %A Lengauer, Thomas %A Pfeifer, Nico %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Effects of Sequencing Errors on Geno2pheno[Coreceptor] Predictions : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0015-7A85-A %F OTHER: Local-ID: E65A7D34540A5DBAC1257C6A004EF397-Pironti2013z %D 2013 %B 11th European Workshop on HIV & Hepatitis %Z date of event: 2013-03-20 - 2013-03-22 %C Rome, Italy %B Abstract Book 11th European Meeting on HIV & Hepatitis Treatment Strategies & Antiviral Drug Resistance %P 23 - 24 %Z sequence number: Abstract O_21 %I Virology Education %J Reviews in Antiviral Therapy & Infectious Diseases %V 13-2
153. Portsmouth S, Valluri SR, Daeumer M, Thiele B, Valdez H, Lewis M, Craig C, Thielen A, James I, Demarest J, Heera J: Correlation between Genotypic (V3 population sequencing) and Phenotypic (Trofile ES) Methods of Characterizing Co-Receptor Usage of HIV-1 from 200 Treatment-naïve HIV Patients Screened for Study A4001078. Antiviral Research 2013, 97.
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@article{Thielen2013z, TITLE = {Correlation between Genotypic ({V3} population sequencing) and Phenotypic (Trofile {ES}) Methods of Characterizing Co-Receptor Usage of {HIV-1} from 200 Treatment-na\"ive {HIV} Patients Screened for Study {A4001078}}, AUTHOR = {Portsmouth, Simon and Valluri, Srinivas Rao and Daeumer, Martin and Thiele, Bernhard and Valdez, Herman and Lewis, Marilyn and Craig, Charles and Thielen, Alexander and James, Ian and Demarest, James and Heera, Jayvant}, LANGUAGE = {eng}, ISSN = {0166-3542}, DOI = {10.1016/j.antiviral.2012.11.002}, PUBLISHER = {Elsevier}, ADDRESS = {Amsterdam}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, DATE = {2013}, JOURNAL = {Antiviral Research}, VOLUME = {97}, NUMBER = {1}, PAGES = {60--65}, }
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%0 Journal Article %A Portsmouth, Simon %A Valluri, Srinivas Rao %A Daeumer, Martin %A Thiele, Bernhard %A Valdez, Herman %A Lewis, Marilyn %A Craig, Charles %A Thielen, Alexander %A James, Ian %A Demarest, James %A Heera, Jayvant %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations %T Correlation between Genotypic (V3 population sequencing) and Phenotypic (Trofile ES) Methods of Characterizing Co-Receptor Usage of HIV-1 from 200 Treatment-naïve HIV Patients Screened for Study A4001078 : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0018-A78C-B %R 10.1016/j.antiviral.2012.11.002 %7 2012 %D 2013 %J Antiviral Research %O Antiviral Res. %V 97 %N 1 %& 60 %P 60 - 65 %I Elsevier %C Amsterdam %@ false
154. Pou C, Codoner francisco M, Thielen A, Bellido R, Perez-Alvarez S, Cabrera C, Dalmau J, Curriu M, Lie Y, Noguera-Julian M, Puig J, Martinez-Picadao J, Blanco J, Daumer M, Clotet B, Paredes R: HIV-1 Tropism Testing in Subjects Achieving Undetectable HIV-1 RNA: Diagnostic Accuracy, Viral Evolution and Compartmentalization. PLoS One 2013, 8.
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@article{Thielen2013, TITLE = {{HIV-1} Tropism Testing in Subjects Achieving Undetectable {HIV-1 RNA}: Diagnostic Accuracy, Viral Evolution and Compartmentalization}, AUTHOR = {Pou, Christian and Codoner, francisco M. and Thielen, Alexander and Bellido, Rocio and Perez-Alvarez, Susana and Cabrera, Cecilia and Dalmau, Judith and Curriu, Marta and Lie, Yolanda and Noguera-Julian, Marc and Puig, Jordi and Martinez-Picadao, Javier and Blanco, Julia and Daumer, Martin and Clotet, Bonaventura and Paredes, Roger}, LANGUAGE = {eng}, ISSN = {1932-6203}, DOI = {10.1371/journal.pone.0067085}, PUBLISHER = {Public Library of Science}, ADDRESS = {San Francisco, CA}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, JOURNAL = {PLoS One}, VOLUME = {8}, NUMBER = {8}, EID = {e67085}, }
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%0 Journal Article %A Pou, Christian %A Codoner, francisco M. %A Thielen, Alexander %A Bellido, Rocio %A Perez-Alvarez, Susana %A Cabrera, Cecilia %A Dalmau, Judith %A Curriu, Marta %A Lie, Yolanda %A Noguera-Julian, Marc %A Puig, Jordi %A Martinez-Picadao, Javier %A Blanco, Julia %A Daumer, Martin %A Clotet, Bonaventura %A Paredes, Roger %+ External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations %T HIV-1 Tropism Testing in Subjects Achieving Undetectable HIV-1 RNA: Diagnostic Accuracy, Viral Evolution and Compartmentalization : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0018-A9E9-7 %R 10.1371/journal.pone.0067085 %7 2013-08-01 %D 2013 %8 01.08.2013 %J PLoS One %V 8 %N 8 %Z sequence number: e67085 %I Public Library of Science %C San Francisco, CA %@ false %U http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0067085
155. Radivojac P, Clark WT, Oron TR, Schnoes AM, Wittkop T, Sokolov A, Graim K, Funk C, Verspoor K, Ben-Hur A, Pandey G, Yunes JM, Talwalkar AS, Repo S, Souza ML, Piovesan D, Casadio R, Wang Z, Cheng J, Fang H, Gough J, Koskinen P, Törönen P, Nokso-Koivisto J, Holm L, Cozzetto D, Buchan DWA, Bryson K, Jones DT, Limaye B, et al.: A Large-scale Evaluation of Computational Protein Function Prediction. Nature Methods 2013, 10.
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@article{Sommer2013, TITLE = {A Large-scale Evaluation of Computational Protein Function Prediction}, AUTHOR = {Radivojac, Predrag and Clark, Wyatt T. and Oron, Tal Ronnen and Schnoes, Alexandra M. and Wittkop, Tobias and Sokolov, Artem and Graim, Kiley and Funk, Christopher and Verspoor, Karin and Ben-Hur, Asa and Pandey, Gaurav and Yunes, Jeffrey M. and Talwalkar, Ameet S. and Repo, Susanna and Souza, Michael L. and Piovesan, Damiano and Casadio, Rita and Wang, Zheng and Cheng, Jianlin and Fang, Hai and Gough, Julian and Koskinen, Patrik and T{\"o}r{\"o}nen, Petri and Nokso-Koivisto, Jussi and Holm, Liisa and Cozzetto, Domenico and Buchan, Daniel W. A. and Bryson, Kevin and Jones, David T. and Limaye, Bhakti and Inamdar, Harshal and Datta, Avik and Manjari, Sunitha K. and Joshi, Rajendra and Chitale, Meghana and Kihara, Daisuke and Lisewski, Andreas M. and Erdin, Serkan and Venner, Eric and Lichtarge, Olivier and Rentzsch, Robert and Yang, Haixuan and Romero, Alfonso E. and Bhat, Prajwal and Paccanaro, Alberto and Hamp, Tobias and Kassner, Rebecca and Seemayer, Stefan and Vicedo, Esmeralda and Schaefer, Christian and Achten, Dominik and Auer, Florian and B{\"o}hm, Ariane and Braun, Tatjana and Hecht, Maximilian and Heron, Mark and H{\"o}nigschmid, Peter and Hopf, Thomas and Kaufmann, Stefanie and Kiening, Michael and Krompass, Denis and Landerer, Cedric and Mahlich, Yannick and Roos, Manfred and Bj{\"o}rne, Jari and Salakoski, Tapio and Wong, Andrew and Shatkay, Hagit and Gatzmann, Fanny and Sommer, Ingolf and Wass, Mark N. and Sternberg, Michael J. E. and {\v S}kunca, Nives and Supek, Fran and Bo{\v s}njak, Matko and Panov, Pan{\v c}e and D{\v z}eroski, Sa{\v s}o and {\v S}muc, Tomislav and Kourmpetis, Yiannis A. I. and van Dijk, Aalt D. J. and ter Braak, Cajo J. F. and Zhou, Yuanpeng and Gong, Qingtian and Dong, Xinran and Tian, Weidong and Falda, Marco and Fontana, Paolo and Lavezzo, Enrico and Di Camillo, Barbara and Toppo, Stefano and Lan, Liang and Djuric, Nemanja and Guo, Yuhong and Vucetic, Slobodan and Bairoch, Amos and Linial, Michal and Babbitt, Patricia C. and Brenner, Steven E. and Orengo, Christine and Rost, Burkhard and Mooney, Sean D. and Friedberg, Iddo}, LANGUAGE = {eng}, ISSN = {1548-7091}, DOI = {10.1038/nmeth.2340}, LOCALID = {Local-ID: 0B86C9EE091302D1C1257B47005C687E-Sommer2013}, PUBLISHER = {Nature Pub. Group}, ADDRESS = {New York, NY}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, DATE = {2013}, JOURNAL = {Nature Methods}, VOLUME = {10}, NUMBER = {3}, PAGES = {221--227}, }
Endnote
%0 Journal Article %A Radivojac, Predrag %A Clark, Wyatt T. %A Oron, Tal Ronnen %A Schnoes, Alexandra M. %A Wittkop, Tobias %A Sokolov, Artem %A Graim, Kiley %A Funk, Christopher %A Verspoor, Karin %A Ben-Hur, Asa %A Pandey, Gaurav %A Yunes, Jeffrey M. %A Talwalkar, Ameet S. %A Repo, Susanna %A Souza, Michael L. %A Piovesan, Damiano %A Casadio, Rita %A Wang, Zheng %A Cheng, Jianlin %A Fang, Hai %A Gough, Julian %A Koskinen, Patrik %A Törönen, Petri %A Nokso-Koivisto, Jussi %A Holm, Liisa %A Cozzetto, Domenico %A Buchan, Daniel W. A. %A Bryson, Kevin %A Jones, David T. %A Limaye, Bhakti %A Inamdar, Harshal %A Datta, Avik %A Manjari, Sunitha K. %A Joshi, Rajendra %A Chitale, Meghana %A Kihara, Daisuke %A Lisewski, Andreas M. %A Erdin, Serkan %A Venner, Eric %A Lichtarge, Olivier %A Rentzsch, Robert %A Yang, Haixuan %A Romero, Alfonso E. %A Bhat, Prajwal %A Paccanaro, Alberto %A Hamp, Tobias %A Kassner, Rebecca %A Seemayer, Stefan %A Vicedo, Esmeralda %A Schaefer, Christian %A Achten, Dominik %A Auer, Florian %A Böhm, Ariane %A Braun, Tatjana %A Hecht, Maximilian %A Heron, Mark %A Hönigschmid, Peter %A Hopf, Thomas %A Kaufmann, Stefanie %A Kiening, Michael %A Krompass, Denis %A Landerer, Cedric %A Mahlich, Yannick %A Roos, Manfred %A Björne, Jari %A Salakoski, Tapio %A Wong, Andrew %A Shatkay, Hagit %A Gatzmann, Fanny %A Sommer, Ingolf %A Wass, Mark N. %A Sternberg, Michael J. E. %A Škunca, Nives %A Supek, Fran %A Bošnjak, Matko %A Panov, Panče %A Džeroski, Sašo %A Šmuc, Tomislav %A Kourmpetis, Yiannis A. I. %A van Dijk, Aalt D. J. %A ter Braak, Cajo J. F. %A Zhou, Yuanpeng %A Gong, Qingtian %A Dong, Xinran %A Tian, Weidong %A Falda, Marco %A Fontana, Paolo %A Lavezzo, Enrico %A Di Camillo, Barbara %A Toppo, Stefano %A Lan, Liang %A Djuric, Nemanja %A Guo, Yuhong %A Vucetic, Slobodan %A Bairoch, Amos %A Linial, Michal %A Babbitt, Patricia C. %A Brenner, Steven E. %A Orengo, Christine %A Rost, Burkhard %A Mooney, Sean D. %A Friedberg, Iddo %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations %T A Large-scale Evaluation of Computational Protein Function Prediction : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0015-7BA6-7 %R 10.1038/nmeth.2340 %2 PMC3584181 %F OTHER: Local-ID: 0B86C9EE091302D1C1257B47005C687E-Sommer2013 %7 2013-01-27 %D 2013 %J Nature Methods %V 10 %N 3 %& 221 %P 221 - 227 %I Nature Pub. Group %C New York, NY %@ false %U http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3584181/
156. Röttger R, Kalaghatgi P, Sun P, de Castro Soares S, Azevedo V, Wittkop T, Baumbach J: Density Parameter Estimation for Finding Clusters of Homologous Proteins - Tracing Actinobacterial Pathogenicity Life Styles. Bioinformatics 2013, 29.
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@article{roettger2012density, TITLE = {Density Parameter Estimation for Finding Clusters of Homologous Proteins -- Tracing Actinobacterial Pathogenicity Life Styles}, AUTHOR = {R{\"o}ttger, Richard and Kalaghatgi, Prabhav and Sun, Peng and de Castro Soares, Siomar and Azevedo, Vasco and Wittkop, Tobias and Baumbach, Jan}, LANGUAGE = {eng}, ISSN = {1367-4803}, DOI = {10.1093/bioinformatics/bts653}, LOCALID = {Local-ID: 30B0AE29B59422D6C1257AEE005D0C44-roettger2012density}, PUBLISHER = {Oxford University Press}, ADDRESS = {Oxford, UK}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, DATE = {2013}, JOURNAL = {Bioinformatics}, VOLUME = {29}, NUMBER = {2}, PAGES = {215--222}, }
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%0 Journal Article %A Röttger, Richard %A Kalaghatgi, Prabhav %A Sun, Peng %A de Castro Soares, Siomar %A Azevedo, Vasco %A Wittkop, Tobias %A Baumbach, Jan %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Density Parameter Estimation for Finding Clusters of Homologous Proteins - Tracing Actinobacterial Pathogenicity Life Styles : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0015-7B82-8 %R 10.1093/bioinformatics/bts653 %F OTHER: Local-ID: 30B0AE29B59422D6C1257AEE005D0C44-roettger2012density %7 2012-11-09 %D 2013 %J Bioinformatics %V 29 %N 2 %& 215 %P 215 - 222 %I Oxford University Press %C Oxford, UK %@ false %U http://doi.org/10.1093/bioinformatics/bts653
157. Sandoval J, Mendez-Gonzales J, Nadal E, Chen G, Carmona FJ, Sayols S, Moran S, Heyn H, Vizoso M, Gomez A, Sanchez-Cespedes M, Assenov Y, Müller F, Bock C, Taron M, Mora J, Muscarella LA, Liloglou T, Davies M, Pollan M, Pajares MJ, Torre W, Montuenga LM, Brambilla E, Field JK, Roz L, Lo Iacono M, Scagliotti GV, Rosell R, Beer DG, et al.: A Prognostic DNA Methylation Signature for Stage I Non-Small-Cell Lung Cancer. Journal of Clinical Oncology 2013, 31.
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@article{Sandoval2013, TITLE = {A Prognostic {DNA} Methylation Signature for Stage {I} Non-Small-Cell Lung Cancer}, AUTHOR = {Sandoval, Juan and Mendez-Gonzales, Jesus and Nadal, Ernest and Chen, Guoan and Carmona, F. Javier and Sayols, Sergi and Moran, Sebastian1 and Heyn, Holger and Vizoso, Miguel and Gomez, Antonio and Sanchez-Cespedes, Montse and Assenov, Yassen and M{\"u}ller, Fabian and Bock, Christoph and Taron, Miquel and Mora, Josefina and Muscarella, Lucia A. and Liloglou, Triantafillos and Davies, Michael and Pollan, Marina and Pajares, Maria J. and Torre, Wenceslao and Montuenga, Luis M. and Brambilla, Elisabeth and Field, John K. and Roz, Luca and Lo Iacono, Marco and Scagliotti, Giorgio V. and Rosell, Rafael and Beer, David G. and Esteller, Manel}, LANGUAGE = {eng}, ISSN = {0732-183X}, DOI = {10.1200/JCO.2012.48.5516}, PUBLISHER = {Grune \& Stratton}, ADDRESS = {New York, NY}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, DATE = {2013-11-10}, JOURNAL = {Journal of Clinical Oncology}, VOLUME = {31}, NUMBER = {32}, PAGES = {4140--4147}, }
Endnote
%0 Journal Article %A Sandoval, Juan %A Mendez-Gonzales, Jesus %A Nadal, Ernest %A Chen, Guoan %A Carmona, F. Javier %A Sayols, Sergi %A Moran, Sebastian1 %A Heyn, Holger %A Vizoso, Miguel %A Gomez, Antonio %A Sanchez-Cespedes, Montse %A Assenov, Yassen %A Müller, Fabian %A Bock, Christoph %A Taron, Miquel %A Mora, Josefina %A Muscarella, Lucia A. %A Liloglou, Triantafillos %A Davies, Michael %A Pollan, Marina %A Pajares, Maria J. %A Torre, Wenceslao %A Montuenga, Luis M. %A Brambilla, Elisabeth %A Field, John K. %A Roz, Luca %A Lo Iacono, Marco %A Scagliotti, Giorgio V. %A Rosell, Rafael %A Beer, David G. %A Esteller, Manel %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations %T A Prognostic DNA Methylation Signature for Stage I Non-Small-Cell Lung Cancer : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0015-8513-6 %R 10.1200/JCO.2012.48.5516 %F OTHER: D1543BC91BBA782EC1257C60005FF511-Sandoval2013 %7 2013-09-30 %D 2013 %8 10.11.2013 %J Journal of Clinical Oncology %V 31 %N 32 %& 4140 %P 4140 - 4147 %I Grune & Stratton %C New York, NY %@ false
158. Sangeda RZ, Theys K, Beheydt G, Rhee S-Y, Deforche K, Vercauteren J, Libin P, Imbrechts S, Grossman Z, Camacho RJ, Van Laethem K, Pironti A, Zazzi M, Sönnerborg A, Incardona F, De Luca A, Torti C, Ruiz L, Van de Vijver DAMC, Shafer RW, Bruzzone B, Van Wijngaerden E, Vandamme A-M: HIV-1 Fitness Landscape Models for Indinavir Treatment Pressure Using Observed Evolution in Longitudinal Sequence Data Are Predictive for Treatment Failure. Infection, Genetics and Evolution 2013, 19.
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@article{Pironti2013y, TITLE = {{HIV-1} Fitness Landscape Models for Indinavir Treatment Pressure Using Observed Evolution in Longitudinal Sequence Data Are Predictive for Treatment Failure}, AUTHOR = {Sangeda, Raphael Z. and Theys, Kristof and Beheydt, Gertjan and Rhee, Soo-Yon and Deforche, Koen and Vercauteren, Jurgen and Libin, Pieter and Imbrechts, Stijn and Grossman, Zehava and Camacho, Ricardo J. and Van Laethem, Kristel and Pironti, Alejandro and Zazzi, Maurizio and S{\"o}nnerborg, Anders and Incardona, Francesca and De Luca, Andrea and Torti, Carolo and Ruiz, Lidia and Van de Vijver, David A. M. C. and Shafer, Robert W. and Bruzzone, Bianca and Van Wijngaerden, Eric and Vandamme, Anne-Mieke}, LANGUAGE = {eng}, ISSN = {1567-1348}, DOI = {10.1016/j.meegid.2013.03.014}, LOCALID = {Local-ID: 617103D78A5E4215C1257C6A004E1E2B-Pironti2013}, PUBLISHER = {Elsevier}, ADDRESS = {Amsterdam}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, DATE = {2013}, JOURNAL = {Infection, Genetics and Evolution}, VOLUME = {19}, PAGES = {349--360}, }
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%0 Journal Article %A Sangeda, Raphael Z. %A Theys, Kristof %A Beheydt, Gertjan %A Rhee, Soo-Yon %A Deforche, Koen %A Vercauteren, Jurgen %A Libin, Pieter %A Imbrechts, Stijn %A Grossman, Zehava %A Camacho, Ricardo J. %A Van Laethem, Kristel %A Pironti, Alejandro %A Zazzi, Maurizio %A Sönnerborg, Anders %A Incardona, Francesca %A De Luca, Andrea %A Torti, Carolo %A Ruiz, Lidia %A Van de Vijver, David A. M. C. %A Shafer, Robert W. %A Bruzzone, Bianca %A Van Wijngaerden, Eric %A Vandamme, Anne-Mieke %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations %T HIV-1 Fitness Landscape Models for Indinavir Treatment Pressure Using Observed Evolution in Longitudinal Sequence Data Are Predictive for Treatment Failure : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0015-8477-C %R 10.1016/j.meegid.2013.03.014 %F OTHER: Local-ID: 617103D78A5E4215C1257C6A004E1E2B-Pironti2013 %7 2013-03-21 %D 2013 %J Infection, Genetics and Evolution %V 19 %& 349 %P 349 - 360 %I Elsevier %C Amsterdam %@ false %U http://www.sciencedirect.com/science/article/pii/S1567134813000877
159. Santos AR, Pereira VB, Barbosa E, Baumbach J, Pauling J, Röttger R, Turk MZ, Silva A, Miyoshi A, Azevedo V: Mature Epitope Density - A Strategy for Target Selection Based on Immunoinformatics and Exported Prokaryotic Proteins. BMC Genomics 2013, 14(Suppl 6).
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@article{PaulingRottger2013, TITLE = {Mature Epitope Density -- A Strategy for Target Selection Based on Immunoinformatics and Exported Prokaryotic Proteins}, AUTHOR = {Santos, Anderson R and Pereira, Vanessa Bastos and Barbosa, Eudes and Baumbach, Jan and Pauling, Josch and R{\"o}ttger, Richard and Turk, Meritxell Zurita and Silva, Arthur and Miyoshi, Anderson and Azevedo, Vasco}, LANGUAGE = {eng}, ISSN = {1471-2164}, DOI = {doi:10.1186/1471-2164-14-S6-S4}, PUBLISHER = {BioMed Central}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, JOURNAL = {BMC Genomics}, VOLUME = {14}, NUMBER = {Suppl 6}, EID = {S4}, }
Endnote
%0 Journal Article %A Santos, Anderson R %A Pereira, Vanessa Bastos %A Barbosa, Eudes %A Baumbach, Jan %A Pauling, Josch %A Röttger, Richard %A Turk, Meritxell Zurita %A Silva, Arthur %A Miyoshi, Anderson %A Azevedo, Vasco %+ External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations %T Mature Epitope Density - A Strategy for Target Selection Based on Immunoinformatics and Exported Prokaryotic Proteins : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0018-AAA6-6 %R doi:10.1186/1471-2164-14-S6-S4 %7 2013-10-25 %D 2013 %8 25.10.2013 %J BMC Genomics %V 14 %N Suppl 6 %Z sequence number: S4 %I BioMed Central %@ false %U http://www.biomedcentral.com/1471-2164/14/S6/S4
160. Savenko V: Genotyping Complex Viral Dual Infections Involving Recombinant Forms Using Population-based Sequence Data. Universität des Saarlandes; 2013.
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@mastersthesis{Savenko2013, TITLE = {Genotyping Complex Viral Dual Infections Involving Recombinant Forms Using Population-based Sequence Data}, AUTHOR = {Savenko, Valentin}, LANGUAGE = {eng}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, DATE = {2013}, TYPE = {Bachelor's thesis}, }
Endnote
%0 Thesis %A Savenko, Valentin %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Genotyping Complex Viral Dual Infections Involving Recombinant Forms Using Population-based Sequence Data : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-C285-F %I Universität des Saarlandes %C Saarbrücken %D 2013 %V bachelor %9 bachelor
161. Schatz MC, Taylor J, Schelhorn SE: The DNA60IFX Contest. Genome Biology 2013, 14.
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@article{Schelhorn2013, TITLE = {The {DNA60IFX} Contest}, AUTHOR = {Schatz, Michael C. and Taylor, James and Schelhorn, Sven Eric}, LANGUAGE = {eng}, ISSN = {1465-6906}, URL = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3706964&tool=pmcentrez&rendertype=abstract}, DOI = {10.1186/gb-2013-14-6-124}, PUBLISHER = {BioMed Central Ltd.}, ADDRESS = {London}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, JOURNAL = {Genome Biology}, VOLUME = {14}, NUMBER = {6}, PAGES = {124:1--124:4}, EID = {124}, }
Endnote
%0 Journal Article %A Schatz, Michael C. %A Taylor, James %A Schelhorn, Sven Eric %+ External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T The DNA60IFX Contest : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0015-796A-E %2 3706964 %R 10.1186/gb-2013-14-6-124 %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3706964&tool=pmcentrez&rendertype=abstract %7 2013-06-28 %D 2013 %8 28.06.2013 %J Genome Biology %V 14 %N 6 %& 124:1 %P 124:1 - 124:4 %Z sequence number: 124 %I BioMed Central Ltd. %C London %@ false
162. Schelhorn SE, Fischer M, Tolosi L, Altmüller J, Nürnberg P, Pfister H, Lengauer T, Berthold F: Sensitive Detection of Viral Transcripts in Human Tumor Transcriptomes. PLoS Computational Biology 2013, 9.
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@article{lengauer2013m, TITLE = {Sensitive Detection of Viral Transcripts in Human Tumor Transcriptomes}, AUTHOR = {Schelhorn, Sven Eric and Fischer, Matthias and Tolosi, Laura and Altm{\"u}ller, Janine and N{\"u}rnberg, Peter and Pfister, Herbert and Lengauer, Thomas and Berthold, Frank}, LANGUAGE = {eng}, ISSN = {1553-734X}, URL = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3789765&tool=pmcentrez&rendertype=abstract}, DOI = {10.1371/journal.pcbi.1003228}, LOCALID = {Local-ID: 6C70D4D0F211A917C1257C0B00368971-lengauer2013m}, PUBLISHER = {Public Library of Science}, ADDRESS = {San Francisco, CA}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, JOURNAL = {PLoS Computational Biology}, VOLUME = {9}, NUMBER = {10}, PAGES = {1--17}, EID = {e1003228}, }
Endnote
%0 Journal Article %A Schelhorn, Sven Eric %A Fischer, Matthias %A Tolosi, Laura %A Altmüller, Janine %A Nürnberg, Peter %A Pfister, Herbert %A Lengauer, Thomas %A Berthold, Frank %A contributor: Wilke, Claus O. %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations %T Sensitive Detection of Viral Transcripts in Human Tumor Transcriptomes : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0015-796F-4 %2 3789765 %F OTHER: Local-ID: 6C70D4D0F211A917C1257C0B00368971-lengauer2013m %R 10.1371/journal.pcbi.1003228 %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3789765&tool=pmcentrez&rendertype=abstract %7 2013-10-03 %D 2013 %8 03.10.2013 %J PLoS Computational Biology %V 9 %N 10 %& 1 %P 1 - 17 %Z sequence number: e1003228 %I Public Library of Science %C San Francisco, CA %@ false
163. Schneider T, Hauschild A-C, Baumbach JI, Baumbach J: An Integrative Clinical Database and Diagnostics Platform for Biomarker Identification and Analysis in Ion Mobility Spectra of Human Exhaled Air. Journal of Integrative Bioinformatics 2013, 10.
Abstract
Over the last decade the evaluation of odors and vapors in human breath has gained more and more attention, particularly in the diagnostics of pulmonary diseases. Ion mobility spectrometry coupled with multi-capillary columns (MCC/IMS), is a well known technology for detecting volatile organic compounds (VOCs) in air. It is a comparatively inexpensive, non-invasive, high-throughput method, which is able to handle the moisture that comes with human exhaled air, and allows for characterizing of VOCs in very low concentrations. To identify discriminating compounds as biomarkers, it is necessary to have a clear understanding of the detailed composition of human breath. Therefore, in addition to the clinical studies, there is a need for a flexible and comprehensive centralized data repository, which is capable of gathering all kinds of related information. Moreover, there is a demand for automated data integration and semi-automated data analysis, in particular with regard to the rapid data accumulation, emerging from the high-throughput nature of the MCC/IMS technology. Here, we present a comprehensive database application and analysis platform, which combines metabolic maps with heterogeneous biomedical data in a well-structured manner. The design of the database is based on a hybrid of the entity-attribute-value (EAV) model and the EAV-CR, which incorporates the concepts of classes and relationships. Additionally it offers an intuitive user interface that provides easy and quick access to the platform's functionality: automated data integration and integrity validation, versioning and roll-back strategy, data retrieval as well as semi-automatic data mining and machine learning capabilities. The platform will support MCC/IMS-based biomarker identification and validation. The software, schemata, data sets and further information is publicly available at \urlhttp://imsdb.mpi-inf.mpg.de.
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@article{Hauschild2013d, TITLE = {An Integrative Clinical Database and Diagnostics Platform for Biomarker Identification and Analysis in Ion Mobility Spectra of Human Exhaled Air}, AUTHOR = {Schneider, Till and Hauschild, Anne-Christin and Baumbach, Joerg Ingo and Baumbach, Jan}, LANGUAGE = {eng}, ISSN = {1613-4516}, DOI = {10.2390/biecoll-jib-2013-218}, PUBLISHER = {IMBio}, ADDRESS = {Gatersleben}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, ABSTRACT = {Over the last decade the evaluation of odors and vapors in human breath has gained more and more attention, particularly in the diagnostics of pulmonary diseases. Ion mobility spectrometry coupled with multi-capillary columns (MCC/IMS), is a well known technology for detecting volatile organic compounds (VOCs) in air. It is a comparatively inexpensive, non-invasive, high-throughput method, which is able to handle the moisture that comes with human exhaled air, and allows for characterizing of VOCs in very low concentrations. To identify discriminating compounds as biomarkers, it is necessary to have a clear understanding of the detailed composition of human breath. Therefore, in addition to the clinical studies, there is a need for a flexible and comprehensive centralized data repository, which is capable of gathering all kinds of related information. Moreover, there is a demand for automated data integration and semi-automated data analysis, in particular with regard to the rapid data accumulation, emerging from the high-throughput nature of the MCC/IMS technology. Here, we present a comprehensive database application and analysis platform, which combines metabolic maps with heterogeneous biomedical data in a well-structured manner. The design of the database is based on a hybrid of the entity-attribute-value (EAV) model and the EAV-CR, which incorporates the concepts of classes and relationships. Additionally it offers an intuitive user interface that provides easy and quick access to the platform's functionality: automated data integration and integrity validation, versioning and roll-back strategy, data retrieval as well as semi-automatic data mining and machine learning capabilities. The platform will support MCC/IMS-based biomarker identification and validation. The software, schemata, data sets and further information is publicly available at \urlhttp://imsdb.mpi-inf.mpg.de.}, JOURNAL = {Journal of Integrative Bioinformatics}, VOLUME = {10}, NUMBER = {2}, EID = {218}, }
Endnote
%0 Journal Article %A Schneider, Till %A Hauschild, Anne-Christin %A Baumbach, Joerg Ingo %A Baumbach, Jan %+ External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T An Integrative Clinical Database and Diagnostics Platform for Biomarker Identification and Analysis in Ion Mobility Spectra of Human Exhaled Air : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0015-84CF-8 %R 10.2390/biecoll-jib-2013-218 %7 2013-04-02 %D 2013 %8 02.04.2013 %X Over the last decade the evaluation of odors and vapors in human breath has gained more and more attention, particularly in the diagnostics of pulmonary diseases. Ion mobility spectrometry coupled with multi-capillary columns (MCC/IMS), is a well known technology for detecting volatile organic compounds (VOCs) in air. It is a comparatively inexpensive, non-invasive, high-throughput method, which is able to handle the moisture that comes with human exhaled air, and allows for characterizing of VOCs in very low concentrations. To identify discriminating compounds as biomarkers, it is necessary to have a clear understanding of the detailed composition of human breath. Therefore, in addition to the clinical studies, there is a need for a flexible and comprehensive centralized data repository, which is capable of gathering all kinds of related information. Moreover, there is a demand for automated data integration and semi-automated data analysis, in particular with regard to the rapid data accumulation, emerging from the high-throughput nature of the MCC/IMS technology. Here, we present a comprehensive database application and analysis platform, which combines metabolic maps with heterogeneous biomedical data in a well-structured manner. The design of the database is based on a hybrid of the entity-attribute-value (EAV) model and the EAV-CR, which incorporates the concepts of classes and relationships. Additionally it offers an intuitive user interface that provides easy and quick access to the platform's functionality: automated data integration and integrity validation, versioning and roll-back strategy, data retrieval as well as semi-automatic data mining and machine learning capabilities. The platform will support MCC/IMS-based biomarker identification and validation. The software, schemata, data sets and further information is publicly available at \urlhttp://imsdb.mpi-inf.mpg.de. %J Journal of Integrative Bioinformatics %V 10 %N 2 %Z sequence number: 218 %I IMBio %C Gatersleben %@ false %U http://dx.doi.org/10.2390/biecoll-jib-2013-218
164. Steijger T, Abril JF, Engström PG, Kokocinski F, Akerman M, Alioto T, Ambrosini G, Antonarakis SE, Behr J, Bohnert R, Bucher P, Cloonan N, Derrien T, Djebali S, Du J, Dudoit S, Engström PG, Gerstein M, Gingeras TR, Gonzalez D, Grimmond SM, Habegger L, Iseli C, Jean G, Kahles A, Kokocinski F, Lagarde J, Leng J, Lefebvre G, Lewis S, et al.: Assessment of Transcript Reconstruction Methods for RNA-seq. Nature Methods 2013, 10.
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@article{SchulzC2013, TITLE = {Assessment of Transcript Reconstruction Methods for {RNA-seq}}, AUTHOR = {Steijger, Tamara and Abril, Josep F. and Engstr{\"o}m, P{\"a}r G. and Kokocinski, Felix and Akerman, M. and Alioto, T. and Ambrosini, G. and Antonarakis, S. E. and Behr, J. and Bohnert, R. and Bucher, P. and Cloonan, N. and Derrien, T. and Djebali, S. and Du, J. and Dudoit, S. and Engstr{\"o}m, P. G. and Gerstein, M. and Gingeras, T. R. and Gonzalez, D. and Grimmond, S. M. and Habegger, L. and Iseli, C. and Jean, G. and Kahles, A. and Kokocinski, F. and Lagarde, J. and Leng, J. and Lefebvre, G. and Lewis, S. and Mortazavi, A. and Niermann, P. and R{\"a}tsch, G. and Reymond, A. and Ribeca, P. and Richard, H. and Rougemont, J. and Rozowsky, J. and Sammeth, M. and Sboner, A. and Schulz, Marcel Holger and Searle, S. M. and Solorzano, N. D. and Solovyev, V. and Stanke, M. and Steijger, T. and Stevenson, B. J. and Stockinger, H. and Valsesia, A. and Weese, D. and White, S. and Wold, B. J. and Wu, J. and Wu, T. D. and Zeller, G. and Zerbino, D. and Zhang, M. Q. and Hubbard, Tim J. and Guig{\'o}, Roderic and Harrow, Jennifer and Bertone, Paul}, LANGUAGE = {eng}, ISSN = {1548-7091}, DOI = {10.1038/nmeth.2714}, LOCALID = {Local-ID: 75F13D2139AD2478C1257C6A004F9484-SchulzC2013}, PUBLISHER = {Nature Pub. Group}, ADDRESS = {New York, NY}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, DATE = {2013}, JOURNAL = {Nature Methods}, VOLUME = {10}, NUMBER = {12}, PAGES = {1177--1184}, }
Endnote
%0 Journal Article %A Steijger, Tamara %A Abril, Josep F. %A Engström, Pär G. %A Kokocinski, Felix %A Akerman, M. %A Alioto, T. %A Ambrosini, G. %A Antonarakis, S. E. %A Behr, J. %A Bohnert, R. %A Bucher, P. %A Cloonan, N. %A Derrien, T. %A Djebali, S. %A Du, J. %A Dudoit, S. %A Engström, P. G. %A Gerstein, M. %A Gingeras, T. R. %A Gonzalez, D. %A Grimmond, S. M. %A Habegger, L. %A Iseli, C. %A Jean, G. %A Kahles, A. %A Kokocinski, F. %A Lagarde, J. %A Leng, J. %A Lefebvre, G. %A Lewis, S. %A Mortazavi, A. %A Niermann, P. %A Rätsch, G. %A Reymond, A. %A Ribeca, P. %A Richard, H. %A Rougemont, J. %A Rozowsky, J. %A Sammeth, M. %A Sboner, A. %A Schulz, Marcel Holger %A Searle, S. M. %A Solorzano, N. D. %A Solovyev, V. %A Stanke, M. %A Steijger, T. %A Stevenson, B. J. %A Stockinger, H. %A Valsesia, A. %A Weese, D. %A White, S. %A Wold, B. J. %A Wu, J. %A Wu, T. D. %A Zeller, G. %A Zerbino, D. %A Zhang, M. Q. %A Hubbard, Tim J. %A Guigó, Roderic %A Harrow, Jennifer %A Bertone, Paul %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations %T Assessment of Transcript Reconstruction Methods for RNA-seq : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0015-7A4B-C %R 10.1038/nmeth.2714 %2 PMC3851240 %F OTHER: Local-ID: 75F13D2139AD2478C1257C6A004F9484-SchulzC2013 %7 2013-11-03 %D 2013 %J Nature Methods %V 10 %N 12 %& 1177 %P 1177 - 1184 %I Nature Pub. Group %C New York, NY %@ false %U http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3851240/
165. Tolosi L, Theißen J, Halachev K, Hero B, Berthold F, Lengauer T: A Method for Finding Consensus Breakpoints in the Cancer Genome From Copy Number Data. Bioinformatics 2013, 29.
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@article{lengauer2013l, TITLE = {A Method for Finding Consensus Breakpoints in the Cancer Genome From Copy Number Data}, AUTHOR = {Tolosi, Laura and Thei{\ss}en, Jessica and Halachev, Konstantin and Hero, Barbara and Berthold, Frank and Lengauer, Thomas}, LANGUAGE = {eng}, ISSN = {1367-4803}, DOI = {10.1093/bioinformatics/btt300}, LOCALID = {Local-ID: B1C8C34D9C5C30ACC1257C0B0036298B-lengauer2013l}, PUBLISHER = {Oxford University Press}, ADDRESS = {Oxford, UK}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, DATE = {2013}, JOURNAL = {Bioinformatics}, VOLUME = {29}, NUMBER = {14}, PAGES = {1793--1800}, }
Endnote
%0 Journal Article %A Tolosi, Laura %A Theißen, Jessica %A Halachev, Konstantin %A Hero, Barbara %A Berthold, Frank %A Lengauer, Thomas %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T A Method for Finding Consensus Breakpoints in the Cancer Genome From Copy Number Data : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0015-7C20-B %R 10.1093/bioinformatics/btt300 %F OTHER: Local-ID: B1C8C34D9C5C30ACC1257C0B0036298B-lengauer2013l %7 2013-05-28 %D 2013 %J Bioinformatics %V 29 %N 14 %& 1793 %P 1793 - 1800 %I Oxford University Press %C Oxford, UK %@ false
166. Vermehren A, Welsch C, Elsler U, Vermehren J, Herrmann E, Sarazin C, von Wagner M, Susser S, Hofmann WP, Kronenberger B, Zeuzem S, Mihm U: Investigation of Viral Escape Mutations within HCV p7 During Treatment with Amantadine in Patients with Chronic Hepatitis C. Antiviral Therapy 2013, 18.
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@article{Susser2013, TITLE = {Investigation of Viral Escape Mutations within {HCV} p7 During Treatment with Amantadine in Patients with Chronic Hepatitis {C}}, AUTHOR = {Vermehren, Annika and Welsch, Christoph and Elsler, Ulrike and Vermehren, Johannes and Herrmann, Eva and Sarazin, Christoph and von Wagner, Michael and Susser, Simone and Hofmann, Wolf Peter and Kronenberger, Bernd and Zeuzem, Stefan and Mihm, Ulrike}, LANGUAGE = {eng}, ISSN = {1359-6535}, DOI = {10.3851/IMP2663}, PUBLISHER = {International Medical Press}, ADDRESS = {London}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, JOURNAL = {Antiviral Therapy}, VOLUME = {18}, PAGES = {803--811}, }
Endnote
%0 Journal Article %A Vermehren, Annika %A Welsch, Christoph %A Elsler, Ulrike %A Vermehren, Johannes %A Herrmann, Eva %A Sarazin, Christoph %A von Wagner, Michael %A Susser, Simone %A Hofmann, Wolf Peter %A Kronenberger, Bernd %A Zeuzem, Stefan %A Mihm, Ulrike %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations %T Investigation of Viral Escape Mutations within HCV p7 During Treatment with Amantadine in Patients with Chronic Hepatitis C : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0018-A863-E %R 10.3851/IMP2663 %7 2013 %D 2013 %J Antiviral Therapy %V 18 %& 803 %P 803 - 811 %I International Medical Press %C London %@ false
167. Weimann A, Trukhina Y, Pope PB, Konietzny S, McHardy AC: De Novo Prediction of the Genomic Components and Capabilities for Microbial Plant Biomass Degradation from (meta-)Genomes. Biotechnology for Biofuels 2013, 6.
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@article{WeimannTrukhina2013, TITLE = {De Novo Prediction of the Genomic Components and Capabilities for Microbial Plant Biomass Degradation from (meta-)Genomes}, AUTHOR = {Weimann, Aaron and Trukhina, Yulia and Pope, Philip B. and Konietzny, Sebastian and McHardy, Alice Carolyn}, LANGUAGE = {eng}, DOI = {10.1186/1754-6834-6-24}, PUBLISHER = {BioMed Central}, ADDRESS = {London}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, JOURNAL = {Biotechnology for Biofuels}, VOLUME = {6}, EID = {24}, }
Endnote
%0 Journal Article %A Weimann, Aaron %A Trukhina, Yulia %A Pope, Philip B. %A Konietzny, Sebastian %A McHardy, Alice Carolyn %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Genomics and Epidemiology, MPI for Informatics, Max Planck Society External Organizations Computational Genomics and Epidemiology, MPI for Informatics, Max Planck Society Computational Genomics and Epidemiology, MPI for Informatics, Max Planck Society %T De Novo Prediction of the Genomic Components and Capabilities for Microbial Plant Biomass Degradation from (meta-)Genomes : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0018-A8A4-B %R 10.1186/1754-6834-6-24 %7 2013-02-15 %D 2013 %8 15.02.2013 %J Biotechnology for Biofuels %V 6 %Z sequence number: 24 %I BioMed Central %C London
168. Zakharkina T, Heinzel E, Koczulla RA, Greulich T, Rentz K, Pauling J, Baumbach J, Herrmann M, Grunewald C, Dienemann H, von Müller L, Bals R: Analysis of the Airway Microbiota of Healthy Individuals and Patients with Chronic Obstructive Pulmonary Disease by T-RFLP and Clone Sequencing. PLoS One 2013, 8.
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@article{PaulingBaumbach2013, TITLE = {Analysis of the Airway Microbiota of Healthy Individuals and Patients with Chronic Obstructive Pulmonary Disease by {T-RFLP} and Clone Sequencing}, AUTHOR = {Zakharkina, Tetyana and Heinzel, Elke and Koczulla, Rembert A. and Greulich, Timm and Rentz, Katharina and Pauling, Josch and Baumbach, Jan and Herrmann, Mathias and Grunewald, Christiane and Dienemann, Hendrik and von M{\"u}ller, Lutz and Bals, Robert}, LANGUAGE = {eng}, ISSN = {1932-6203}, DOI = {10.1371/journal.pone.0068302}, PUBLISHER = {Public Library of Science}, ADDRESS = {San Francisco, CA}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, JOURNAL = {PLoS One}, VOLUME = {8}, NUMBER = {7}, EID = {e68302}, }
Endnote
%0 Journal Article %A Zakharkina, Tetyana %A Heinzel, Elke %A Koczulla, Rembert A. %A Greulich, Timm %A Rentz, Katharina %A Pauling, Josch %A Baumbach, Jan %A Herrmann, Mathias %A Grunewald, Christiane %A Dienemann, Hendrik %A von Müller, Lutz %A Bals, Robert %+ External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations %T Analysis of the Airway Microbiota of Healthy Individuals and Patients with Chronic Obstructive Pulmonary Disease by T-RFLP and Clone Sequencing : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0018-A9BE-9 %R 10.1371/journal.pone.0068302 %7 2013-07-09 %D 2013 %8 09.07.2013 %J PLoS One %V 8 %N 7 %Z sequence number: e68302 %I Public Library of Science %C San Francisco, CA %@ false %U http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0068302
169. Zanon A, Rakovic A, Blankenburg H, Doncheva NT, Schwienbacher C, Serafin A, Alexa A, Weichenberger CX, Albrecht M, Klein C, Hicks AA, Pramstaller PP, Domingues FS, Pichler I: Profiling of Parkin-binding Partners Using Tandem Affinity Purification. PLoS One 2013, 8.
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@article{Albrecht2013c, TITLE = {Profiling of {P}arkin-binding Partners Using Tandem Affinity Purification}, AUTHOR = {Zanon, Alessandra and Rakovic, Aleksandar and Blankenburg, Hagen and Doncheva, Nadezhda Tsankova and Schwienbacher, Christine and Serafin, Alice and Alexa, Adrian and Weichenberger, Christian X. and Albrecht, Mario and Klein, Christine and Hicks, Andrew A. and Pramstaller, Peter P. and Domingues, Francisco S. and Pichler, Irene}, LANGUAGE = {eng}, ISSN = {1932-6203}, URL = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3823883&tool=pmcentrez&rendertype=abstract}, DOI = {10.1371/journal.pone.0078648}, LOCALID = {Local-ID: 348090E858FCD2E4C1257C70004DB8FD-Albrecht2013c}, PUBLISHER = {Public Library of Science}, ADDRESS = {San Francisco, CA}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, JOURNAL = {PLoS One}, VOLUME = {8}, NUMBER = {11}, PAGES = {1--17}, EID = {e78648}, }
Endnote
%0 Journal Article %A Zanon, Alessandra %A Rakovic, Aleksandar %A Blankenburg, Hagen %A Doncheva, Nadezhda Tsankova %A Schwienbacher, Christine %A Serafin, Alice %A Alexa, Adrian %A Weichenberger, Christian X. %A Albrecht, Mario %A Klein, Christine %A Hicks, Andrew A. %A Pramstaller, Peter P. %A Domingues, Francisco S. %A Pichler, Irene %A contributor: Westermark, Per %+ External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations %T Profiling of Parkin-binding Partners Using Tandem Affinity Purification : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0015-7987-E %2 3823883 %F OTHER: Local-ID: 348090E858FCD2E4C1257C70004DB8FD-Albrecht2013c %R 10.1371/journal.pone.0078648 %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3823883&tool=pmcentrez&rendertype=abstract %7 2013-11-11 %D 2013 %8 11.11.2013 %J PLoS One %V 8 %N 11 %& 1 %P 1 - 17 %Z sequence number: e78648 %I Public Library of Science %C San Francisco, CA %@ false
170. Ziller MJ, Gu H, Müller F, Donaghey J, Tsai LT-Y, Kohlbacher O, De Jager PL, Rosen ED, Bennett DA, Bernstein BE, Gnirke A, Meissner A: Charting a Dynamic DNA Methylation Landscape of the Human Genome. Nature 2013, 500.
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@article{Ziller2013, TITLE = {Charting a Dynamic {DNA} Methylation Landscape of the Human Genome}, AUTHOR = {Ziller, Michael J. and Gu, Hongcang and M{\"u}ller, Fabian and Donaghey, Julie and Tsai, Linus T.-Y. and Kohlbacher, Oliver and De Jager, Philip L. and Rosen, Evan D. and Bennett, David A. and Bernstein, Bradley E. and Gnirke, Andreas and Meissner, Alexander}, LANGUAGE = {eng}, ISSN = {0028-0836}, DOI = {10.1038/nature12433}, LOCALID = {Local-ID: 6CAEAA3794FDEA3BC1257C6000605839-Ziller2013}, PUBLISHER = {Nature Publishing Group}, ADDRESS = {London}, YEAR = {2013}, MARGINALMARK = {$\bullet$}, DATE = {2013}, JOURNAL = {Nature}, VOLUME = {500}, NUMBER = {7463}, PAGES = {477--481}, }
Endnote
%0 Journal Article %A Ziller, Michael J. %A Gu, Hongcang %A Müller, Fabian %A Donaghey, Julie %A Tsai, Linus T.-Y. %A Kohlbacher, Oliver %A De Jager, Philip L. %A Rosen, Evan D. %A Bennett, David A. %A Bernstein, Bradley E. %A Gnirke, Andreas %A Meissner, Alexander %+ External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations %T Charting a Dynamic DNA Methylation Landscape of the Human Genome : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0015-851A-7 %R 10.1038/nature12433 %2 PMC3821869 %F OTHER: Local-ID: 6CAEAA3794FDEA3BC1257C6000605839-Ziller2013 %7 2013-08-07 %D 2013 %J Nature %V 500 %N 7463 %& 477 %P 477 - 481 %I Nature Publishing Group %C London %@ false
2012
171. Adams D, Altucci L, Antonarakis SE, Ballesteros J, Beck S, Bird A, Bock C, Boehm B, Campo E, Caricasole A, Dahl F, Dermitzakis ET, Enver T, Esteller M, Estivill X, Ferguson-Smith A, Fitzgibbon J, Flicek P, Giehl C, Graf T, Grosveld F, Guigo R, Gut I, Helin K, Jarvius J, Küppers R, Lehrach H, Lengauer T, Lernmark A, Leslie D, et al.: BLUEPRINT to Decode the Epigenetic Signature Written in Blood. Nature biotechnology 2012, 30.
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@article{Adams2012, TITLE = {{BLUEPRINT} to Decode the Epigenetic Signature Written in Blood}, AUTHOR = {Adams, David and Altucci, Lucia and Antonarakis, Stylionos E. and Ballesteros, Juan and Beck, Stephan and Bird, Adrian and Bock, Christoph and Boehm, Bernhard and Campo, Elias and Caricasole, Andrea and Dahl, Frederik and Dermitzakis, Emmanouil T. and Enver, Tariq and Esteller, Manel and Estivill, Xavier and Ferguson-Smith, Anne and Fitzgibbon, Jude and Flicek, Paul and Giehl, Claudia and Graf, Thomas and Grosveld, Frank and Guigo, Roderic and Gut, Ivo and Helin, Kristian and Jarvius, Jonas and K{\"u}ppers, Ralf and Lehrach, Hans and Lengauer, Thomas and Lernmark, Ake and Leslie, David and Loeffler, Markus and Macintyre, Elizabeth and Mai, Antonello and Martens, Joost H. A. and Minucci, Saverio and Ouwehand, Willem H. and Pelicci, Pier Giuseppe and Pendeville, H{\`e}l{\'e}ne and Porse, Bo and Rakyan, Vardham and Reik, Wolf and Schrappe, Martin and Sch{\"u}beler, Dirk and Seifert, Martin and Siebert, Reiner and Simmons, David and Soranzo, Nicole and Spicuglia, Salvatore and Stratton, Michael and Stunnenberg, Hendrik G. and Tanay, Amos and Torrents, David and Valencia, Alfonso and Vellenga, Edo and Vingron, Martin and Walter, J{\"o}rn and Willcocks, Spike}, LANGUAGE = {eng}, ISSN = {1087-0156; 1546-1696}, URL = {http://www.ncbi.nlm.nih.gov/pubmed/22398613}, DOI = {10.1038/nbt.2153}, LOCALID = {Local-ID: 9989EDB3AC4E86A0C1257B02002F3253-Adams2012}, PUBLISHER = {Nature Publishing Group}, ADDRESS = {New York, NY}, YEAR = {2012}, DATE = {2012}, JOURNAL = {Nature biotechnology}, VOLUME = {30}, NUMBER = {3}, PAGES = {224--226}, }
Endnote
%0 Journal Article %A Adams, David %A Altucci, Lucia %A Antonarakis, Stylionos E. %A Ballesteros, Juan %A Beck, Stephan %A Bird, Adrian %A Bock, Christoph %A Boehm, Bernhard %A Campo, Elias %A Caricasole, Andrea %A Dahl, Frederik %A Dermitzakis, Emmanouil T. %A Enver, Tariq %A Esteller, Manel %A Estivill, Xavier %A Ferguson-Smith, Anne %A Fitzgibbon, Jude %A Flicek, Paul %A Giehl, Claudia %A Graf, Thomas %A Grosveld, Frank %A Guigo, Roderic %A Gut, Ivo %A Helin, Kristian %A Jarvius, Jonas %A Küppers, Ralf %A Lehrach, Hans %A Lengauer, Thomas %A Lernmark, Ake %A Leslie, David %A Loeffler, Markus %A Macintyre, Elizabeth %A Mai, Antonello %A Martens, Joost H. A. %A Minucci, Saverio %A Ouwehand, Willem H. %A Pelicci, Pier Giuseppe %A Pendeville, Hèléne %A Porse, Bo %A Rakyan, Vardham %A Reik, Wolf %A Schrappe, Martin %A Schübeler, Dirk %A Seifert, Martin %A Siebert, Reiner %A Simmons, David %A Soranzo, Nicole %A Spicuglia, Salvatore %A Stratton, Michael %A Stunnenberg, Hendrik G. %A Tanay, Amos %A Torrents, David %A Valencia, Alfonso %A Vellenga, Edo %A Vingron, Martin %A Walter, Jörn %A Willcocks, Spike %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations %T BLUEPRINT to Decode the Epigenetic Signature Written in Blood : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-D20B-B %F OTHER: Local-ID: 9989EDB3AC4E86A0C1257B02002F3253-Adams2012 %R 10.1038/nbt.2153 %U http://www.ncbi.nlm.nih.gov/pubmed/22398613 %7 2012-03-07 %D 2012 %K Animals Blood Cells/classification/cytology/metabolism *Epigenesis, Genetic Genome Humans RNA Interference *Societies, Scientific %J Nature biotechnology %V 30 %N 3 %& 224 %P 224 - 226 %I Nature Publishing Group %C New York, NY %@ false
172. Alcaraz Milman N: KeyPathwayMiner - Detecting Case-specific Biological Pathways by Using Expression Data. Universität des Saarlandes; 2012.
Abstract
Advances in the field of systems biology have provided the biological community with massive amounts of pathway data that describe the interplay of genes and their products. The resulting biological networks usually consist of thousands of entities and interactions that can be modeled mathematically as graphs. Since these networks only provide a static picture of the accumulated knowledge, pathways that are affected during development of complex diseases cannot be extracted easily. This gap can be lled by means of OMICS technologies such as DNA microarrays, which measure the activity of genes and proteins under different conditions. Integration of both interaction and expression datasets can increase the quality and accuracy of analysis when compared to independant inspection of each. However, sophisticated computational methods are needed to deal with the size of the datasets while also accounting for the presence of biological and technological noise inherent in the data generating process. In this dissertation the KeyPathwayMiner is presented, a method that enables the extraction and visualization of affected pathways given the results of a series of gene expression studies. Specically, given network and gene expression data, KeyPathwayMiner identies those maximal subgraphs where all but k nodes of the subnetwork are differentially expressed in all but at most l cases in the gene expression data. This new formulation allows users to control the number of outliers with two parameters that provide good interpretability of the solutions. Since identifying these subgraphs is computationally intensive, an heuristic algorithm based on Ant Colony Optimization was designed and adapted to this problem, where solutions are reported in the order of seconds on a standard personal computer. The Key-PathwayMiner was tested on real Huntingtons Disease and Breast Cancer datasets, where it is able to extract pathways containing a large percentage of known relevant genes when compared to other similar approaches. KeyPathwayMiner has been implemented as a plugin for Cytoscape, one of the most widely used open source biological network analysis and visualization platforms. The Key-PathwayMiner is available online at http://keypathwayminer.mpi-inf.mpg.de or through the plugin manager of Cytoscape.
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@mastersthesis{AlcarazMilman2012, TITLE = {{K}ey{P}athway{M}iner -- Detecting Case-specific Biological Pathways by Using Expression Data}, AUTHOR = {Alcaraz Milman, Nicolas}, LANGUAGE = {eng}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2012}, DATE = {2012}, ABSTRACT = {Advances in the field of systems biology have provided the biological community with massive amounts of pathway data that describe the interplay of genes and their products. The resulting biological networks usually consist of thousands of entities and interactions that can be modeled mathematically as graphs. Since these networks only provide a static picture of the accumulated knowledge, pathways that are affected during development of complex diseases cannot be extracted easily. This gap can be lled by means of OMICS technologies such as DNA microarrays, which measure the activity of genes and proteins under different conditions. Integration of both interaction and expression datasets can increase the quality and accuracy of analysis when compared to independant inspection of each. However, sophisticated computational methods are needed to deal with the size of the datasets while also accounting for the presence of biological and technological noise inherent in the data generating process. In this dissertation the KeyPathwayMiner is presented, a method that enables the extraction and visualization of affected pathways given the results of a series of gene expression studies. Specically, given network and gene expression data, KeyPathwayMiner identies those maximal subgraphs where all but k nodes of the subnetwork are differentially expressed in all but at most l cases in the gene expression data. This new formulation allows users to control the number of outliers with two parameters that provide good interpretability of the solutions. Since identifying these subgraphs is computationally intensive, an heuristic algorithm based on Ant Colony Optimization was designed and adapted to this problem, where solutions are reported in the order of seconds on a standard personal computer. The Key-PathwayMiner was tested on real Huntingtons Disease and Breast Cancer datasets, where it is able to extract pathways containing a large percentage of known relevant genes when compared to other similar approaches. KeyPathwayMiner has been implemented as a plugin for Cytoscape, one of the most widely used open source biological network analysis and visualization platforms. The Key-PathwayMiner is available online at http://keypathwayminer.mpi-inf.mpg.de or through the plugin manager of Cytoscape.}, }
Endnote
%0 Thesis %A Alcaraz Milman, Nicolas %Y Baumbach, Jan %A referee: Helms, Volkhard %+ International Max Planck Research School, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T KeyPathwayMiner - Detecting Case-specific Biological Pathways by Using Expression Data : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0026-CC8A-B %I Universität des Saarlandes %C Saarbrücken %D 2012 %V master %9 master %X Advances in the field of systems biology have provided the biological community with massive amounts of pathway data that describe the interplay of genes and their products. The resulting biological networks usually consist of thousands of entities and interactions that can be modeled mathematically as graphs. Since these networks only provide a static picture of the accumulated knowledge, pathways that are affected during development of complex diseases cannot be extracted easily. This gap can be lled by means of OMICS technologies such as DNA microarrays, which measure the activity of genes and proteins under different conditions. Integration of both interaction and expression datasets can increase the quality and accuracy of analysis when compared to independant inspection of each. However, sophisticated computational methods are needed to deal with the size of the datasets while also accounting for the presence of biological and technological noise inherent in the data generating process. In this dissertation the KeyPathwayMiner is presented, a method that enables the extraction and visualization of affected pathways given the results of a series of gene expression studies. Specically, given network and gene expression data, KeyPathwayMiner identies those maximal subgraphs where all but k nodes of the subnetwork are differentially expressed in all but at most l cases in the gene expression data. This new formulation allows users to control the number of outliers with two parameters that provide good interpretability of the solutions. Since identifying these subgraphs is computationally intensive, an heuristic algorithm based on Ant Colony Optimization was designed and adapted to this problem, where solutions are reported in the order of seconds on a standard personal computer. The Key-PathwayMiner was tested on real Huntingtons Disease and Breast Cancer datasets, where it is able to extract pathways containing a large percentage of known relevant genes when compared to other similar approaches. KeyPathwayMiner has been implemented as a plugin for Cytoscape, one of the most widely used open source biological network analysis and visualization platforms. The Key-PathwayMiner is available online at http://keypathwayminer.mpi-inf.mpg.de or through the plugin manager of Cytoscape.
173. Alcaraz N, Kucuk H, Weile J, Wipat A, Baumbach J: KeyPathwayMiner - Detecting Case-specific Biological Pathways by Using Expression Data. Internet Mathematics 2012, 7.
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@article{Baumbach2011g, TITLE = {{KeyPathwayMiner} -- Detecting Case-specific Biological Pathways by Using Expression Data}, AUTHOR = {Alcaraz, Nicolas and Kucuk, Hande and Weile, Jochen and Wipat, Anil and Baumbach, Jan}, LANGUAGE = {eng}, ISSN = {1542-7951; 1944-9488}, DOI = {10.1080/15427951.2011.604548}, LOCALID = {Local-ID: 1AB729ED38458292C125798400529F56-Baumbach2011g}, PUBLISHER = {Peters}, ADDRESS = {Natick, Mass.}, YEAR = {2012}, DATE = {2012}, JOURNAL = {Internet Mathematics}, VOLUME = {7}, NUMBER = {4}, PAGES = {299--313}, JOURNAL = {Biological Networks}, EDITOR = {Przulj, Natasa}, }
Endnote
%0 Journal Article %A Alcaraz, Nicolas %A Kucuk, Hande %A Weile, Jochen %A Wipat, Anil %A Baumbach, Jan %+ External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T KeyPathwayMiner - Detecting Case-specific Biological Pathways by Using Expression Data : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-C584-4 %R 10.1080/15427951.2011.604548 %F OTHER: Local-ID: 1AB729ED38458292C125798400529F56-Baumbach2011g %7 2011-11-30 %D 2012 %J Internet Mathematics %V 7 %N 4 %& 299 %P 299 - 313 %I Peters %C Natick, Mass. %@ false %B Biological Networks %U http://projecteuclid.org/euclid.im/1323367282
174. Alcaraz N, Friedrich T, Kötzing T, Müller J, Pauling J, Baumbach J: Efficient Key Pathway Mining: Combining Networks and OMICS Data. Integrative Biology 2012, 4.
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@article{AlcarayFKKMPB2012, TITLE = {Efficient Key Pathway Mining: Combining Networks and {OMICS} Data}, AUTHOR = {Alcaraz, Nicolas and Friedrich, Tobias and K{\"o}tzing, Timo and M{\"u}ller, Joachim and Pauling, Josch and Baumbach, Jan}, LANGUAGE = {eng}, ISSN = {1757-9694}, DOI = {10.1039/C2IB00133K}, LOCALID = {Local-ID: 838EF16B927A5642C1257AC6004F073E-AlcarayFKKMPB2012}, PUBLISHER = {The Royal Society of Chemistry}, ADDRESS = {London, UK}, YEAR = {2012}, DATE = {2012}, JOURNAL = {Integrative Biology}, VOLUME = {4}, NUMBER = {7}, PAGES = {756--764}, }
Endnote
%0 Journal Article %A Alcaraz, Nicolas %A Friedrich, Tobias %A Kötzing, Timo %A Müller, Joachim %A Pauling, Josch %A Baumbach, Jan %+ Cluster of Excellence Multimodal Computing and Interaction Algorithms and Complexity, MPI for Informatics, Max Planck Society Algorithms and Complexity, MPI for Informatics, Max Planck Society Cluster of Excellence Multimodal Computing and Interaction Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Efficient Key Pathway Mining: Combining Networks and OMICS Data : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-C4FE-9 %F OTHER: Local-ID: 838EF16B927A5642C1257AC6004F073E-AlcarayFKKMPB2012 %R 10.1039/C2IB00133K %7 2012-02-21 %D 2012 %J Integrative Biology %V 4 %N 7 %& 756 %P 756 - 764 %I The Royal Society of Chemistry %C London, UK %@ false
175. Bader M: Clustering Epigenetic Data Using a Dirichlet Process Prior. Universität des Saarlandes; 2012.
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@mastersthesis{BaderMaster2012, TITLE = {Clustering Epigenetic Data Using a {Dirichlet} Process Prior}, AUTHOR = {Bader, Mathias}, LANGUAGE = {eng}, LOCALID = {Local-ID: E8A202C2006A8F23C1257B2700542135-BaderMaster2012}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2012}, DATE = {2012}, }
Endnote
%0 Thesis %A Bader, Mathias %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Clustering Epigenetic Data Using a Dirichlet Process Prior : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-BA44-B %F OTHER: Local-ID: E8A202C2006A8F23C1257B2700542135-BaderMaster2012 %I Universität des Saarlandes %C Saarbrücken %D 2012 %V master %9 master
176. Bastys T: MAP Kinase Docking Motifs in HIV Proteins. Universität des Saarlandes; 2012.
Abstract
After 30 years of research, acquired immunodeficiency syndrome (AIDS) is still considered a pandemic and has no cure. Human immunodeficiency virus (HIV), which causes the disease, depends on the cellular protein machinery to replicate in the host cells. It has been suggested by different studies to employ mitogen-activated protein kinases (MAPKs), enzyme active in cell signalling, among other proteins. For its target recognition, MAPKs use a site on their surface separate from their active site, which recognises and docks with short linear motifs. This is a promising lead for targeting with drugs to inhibit HIV replication. In this work the presence of such motifs was investigated in HIV proteins. Identified motifs were evaluated statistically. Afterwords selected candidates were modelled in complex with MAPK and docked. Additionally, the conservation of such motifs in HIV protein sequences was analysed to gain insight into evolution of MAPK docking motifs in HIV.
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@mastersthesis{Bastys2012, TITLE = {{MAP} Kinase Docking Motifs in {HIV} Proteins}, AUTHOR = {Bastys, Tomas}, LANGUAGE = {eng}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2012}, DATE = {2012}, ABSTRACT = {After 30 years of research, acquired immunodeficiency syndrome (AIDS) is still considered a pandemic and has no cure. Human immunodeficiency virus (HIV), which causes the disease, depends on the cellular protein machinery to replicate in the host cells. It has been suggested by different studies to employ mitogen-activated protein kinases (MAPKs), enzyme active in cell signalling, among other proteins. For its target recognition, MAPKs use a site on their surface separate from their active site, which recognises and docks with short linear motifs. This is a promising lead for targeting with drugs to inhibit HIV replication. In this work the presence of such motifs was investigated in HIV proteins. Identified motifs were evaluated statistically. Afterwords selected candidates were modelled in complex with MAPK and docked. Additionally, the conservation of such motifs in HIV protein sequences was analysed to gain insight into evolution of MAPK docking motifs in HIV.}, }
Endnote
%0 Thesis %A Bastys, Tomas %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T MAP Kinase Docking Motifs in HIV Proteins : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-BB01-A %F OTHER: C3FC38B8C7592CE8C1257AF60049E3A2-Bastys2012 %I Universität des Saarlandes %C Saarbrücken %D 2012 %V master %9 master %X After 30 years of research, acquired immunodeficiency syndrome (AIDS) is still considered a pandemic and has no cure. Human immunodeficiency virus (HIV), which causes the disease, depends on the cellular protein machinery to replicate in the host cells. It has been suggested by different studies to employ mitogen-activated protein kinases (MAPKs), enzyme active in cell signalling, among other proteins. For its target recognition, MAPKs use a site on their surface separate from their active site, which recognises and docks with short linear motifs. This is a promising lead for targeting with drugs to inhibit HIV replication. In this work the presence of such motifs was investigated in HIV proteins. Identified motifs were evaluated statistically. Afterwords selected candidates were modelled in complex with MAPK and docked. Additionally, the conservation of such motifs in HIV protein sequences was analysed to gain insight into evolution of MAPK docking motifs in HIV.
177. Baumbach J, Friedrich T, Kötzing T, Krohmer A, Müller J, Pauling J: Efficient Algorithms for Extracting Biological Key Pathways with Global Constraints. In GECCO’12, Fourteenth International Conference on Genetic and Evolutionary Computation. ACM; 2012.
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@inproceedings{BaumbachFKKMP2011, TITLE = {Efficient Algorithms for Extracting Biological Key Pathways with Global Constraints}, AUTHOR = {Baumbach, Jan and Friedrich, Tobias and K{\"o}tzing, Timo and Krohmer, Anton and M{\"u}ller, Joachim and Pauling, Josch}, LANGUAGE = {eng}, ISBN = {978-1-4503-1177-9}, DOI = {10.1145/2330163.2330188}, LOCALID = {Local-ID: AA1A2CBB406CE65DC1257AC6004CAB27-BaumbachFKKMP2011}, PUBLISHER = {ACM}, YEAR = {2012}, DATE = {2012}, BOOKTITLE = {GECCO'12, Fourteenth International Conference on Genetic and Evolutionary Computation}, EDITOR = {Soule, Terence}, PAGES = {169--176}, ADDRESS = {Philadelphia, PA}, }
Endnote
%0 Conference Proceedings %A Baumbach, Jan %A Friedrich, Tobias %A Kötzing, Timo %A Krohmer, Anton %A Müller, Joachim %A Pauling, Josch %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Algorithms and Complexity, MPI for Informatics, Max Planck Society Algorithms and Complexity, MPI for Informatics, Max Planck Society External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Efficient Algorithms for Extracting Biological Key Pathways with Global Constraints : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-BB66-6 %R 10.1145/2330163.2330188 %F OTHER: Local-ID: AA1A2CBB406CE65DC1257AC6004CAB27-BaumbachFKKMP2011 %D 2012 %B Fourteenth International Conference on Genetic and Evolutionary Computation %Z date of event: 2012-07-07 - 2012-07-12 %C Philadelphia, PA %B GECCO'12 %E Soule, Terence %P 169 - 176 %I ACM %@ 978-1-4503-1177-9
178. Baumbach J: Integrative Computational Biology. Integrative Biology : quantitative biosciences from nano to macro 2012, 4.
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@article{Baumbach2012, TITLE = {Integrative Computational Biology}, AUTHOR = {Baumbach, Jan}, LANGUAGE = {eng}, ISSN = {1757-9708; 1757-9694}, URL = {http://www.ncbi.nlm.nih.gov/pubmed/22706452}, DOI = {10.1039/c2ib90016e}, LOCALID = {Local-ID: B690C55C9B9D9377C1257B2800358BFD-Baumbach2012}, PUBLISHER = {Royal Society of Chemistry}, ADDRESS = {London}, YEAR = {2012}, DATE = {2012}, JOURNAL = {Integrative Biology : quantitative biosciences from nano to macro}, VOLUME = {4}, NUMBER = {7}, PAGES = {713--714}, }
Endnote
%0 Journal Article %A Baumbach, Jan %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Integrative Computational Biology : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-D209-F %F OTHER: Local-ID: B690C55C9B9D9377C1257B2800358BFD-Baumbach2012 %R 10.1039/c2ib90016e %U http://www.ncbi.nlm.nih.gov/pubmed/22706452 %7 2012-06-15 %D 2012 %K Animals Bacterial Physiological Phenomena Computational Biology/*methods Computer Systems DNA Barcoding, Taxonomic Databases, Factual Genes, Bacterial Genomics Humans Protein Interaction Mapping Proteomics/methods Software Systems Biology %J Integrative Biology : quantitative biosciences from nano to macro %O Integr Biol %V 4 %N 7 %& 713 %P 713 - 714 %I Royal Society of Chemistry %C London %@ false
179. Beggel B, Neumann-Fraune M, Döring M, Lawyer G, Kaiser R, Verheyen J, Lengauer T: Genotyping Hepatitis B Virus Dual Infections Using Population-based Sequence Data. Journal of General Virology 2012, 93.
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@article{Beggel2012, TITLE = {Genotyping Hepatitis {B} Virus Dual Infections Using Population-based Sequence Data}, AUTHOR = {Beggel, Bastian and Neumann-Fraune, Maria and D{\"o}ring, Matthias and Lawyer, Glenn and Kaiser, Rolf and Verheyen, Jens and Lengauer, Thomas}, LANGUAGE = {eng}, ISSN = {0022-1317}, DOI = {10.1099/vir.0.043042-0}, LOCALID = {Local-ID: 497568B14391E344C1257AD30047BB4A-Beggel2012}, PUBLISHER = {Society for General Microbiology [etc.]}, ADDRESS = {London [etc.]}, YEAR = {2012}, DATE = {2012}, JOURNAL = {Journal of General Virology}, VOLUME = {93}, NUMBER = {9}, PAGES = {1899--1907}, }
Endnote
%0 Journal Article %A Beggel, Bastian %A Neumann-Fraune, Maria %A Döring, Matthias %A Lawyer, Glenn %A Kaiser, Rolf %A Verheyen, Jens %A Lengauer, Thomas %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Genotyping Hepatitis B Virus Dual Infections Using Population-based Sequence Data : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-D1FC-6 %R 10.1099/vir.0.043042-0 %F OTHER: Local-ID: 497568B14391E344C1257AD30047BB4A-Beggel2012 %7 2012-06-13 %D 2012 %J Journal of General Virology %V 93 %N 9 %& 1899 %P 1899 - 1907 %I Society for General Microbiology [etc.] %C London [etc.] %@ false %U http://vir.sgmjournals.org/content/93/Pt_9/1899
180. Bhattacharyya M, Feuerbach L, Bhadra T, Lengauer T, Bandyopadhyay S: MicroRNA Transcription Start Site Prediction with Multi-objective Feature Selection. Statistical Applications in Genetics and Molecular Biology 2012, 11.
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@article{Bandyopadhyay2011, TITLE = {{MicroRNA} Transcription Start Site Prediction with Multi-objective Feature Selection}, AUTHOR = {Bhattacharyya, Malay and Feuerbach, Lars and Bhadra, Tapas and Lengauer, Thomas and Bandyopadhyay, Sanghamitra}, LANGUAGE = {eng}, ISSN = {1544-6115}, DOI = {10.2202/1544-6115.1743}, LOCALID = {Local-ID: F45F4EE51DD4C2E1C12579DD0034CA49-Bandyopadhyay2011}, PUBLISHER = {Berkeley Electronic Press}, ADDRESS = {Berkeley, CA}, YEAR = {2012}, JOURNAL = {Statistical Applications in Genetics and Molecular Biology}, VOLUME = {11}, NUMBER = {1}, PAGES = {6:1--6:25}, EID = {6}, }
Endnote
%0 Journal Article %A Bhattacharyya, Malay %A Feuerbach, Lars %A Bhadra, Tapas %A Lengauer, Thomas %A Bandyopadhyay, Sanghamitra %+ External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T MicroRNA Transcription Start Site Prediction with Multi-objective Feature Selection : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-D1ED-A %R 10.2202/1544-6115.1743 %F OTHER: Local-ID: F45F4EE51DD4C2E1C12579DD0034CA49-Bandyopadhyay2011 %7 2012-01-06 %D 2012 %8 06.01.2012 %J Statistical Applications in Genetics and Molecular Biology %V 11 %N 1 %& 6:1 %P 6:1 - 6:25 %Z sequence number: 6 %I Berkeley Electronic Press %C Berkeley, CA %@ false
181. Bock C: Analysing and Interpreting DNA Methylation Data. Nature Reviews Genetics 2012, 13.
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@article{Bock2012a, TITLE = {Analysing and Interpreting {DNA} Methylation Data}, AUTHOR = {Bock, Christoph}, LANGUAGE = {eng}, DOI = {10.1038/nrg3273}, LOCALID = {Local-ID: F8E71752F0550117C1257AED00400B82-Bock2012a}, PUBLISHER = {Nature Publishing Group}, ADDRESS = {New York, NY}, YEAR = {2012}, DATE = {2012}, JOURNAL = {Nature Reviews Genetics}, VOLUME = {13}, NUMBER = {10}, PAGES = {705--719}, }
Endnote
%0 Journal Article %A Bock, Christoph %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Analysing and Interpreting DNA Methylation Data : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-BB5B-F %R 10.1038/nrg3273 %F OTHER: Local-ID: F8E71752F0550117C1257AED00400B82-Bock2012a %D 2012 %J Nature Reviews Genetics %V 13 %N 10 %& 705 %P 705 - 719 %I Nature Publishing Group %C New York, NY
182. Bock C, Lengauer T: Managing Drug Resistance in Cancer: {Lessons} from {HIV} Therapy. Nature Reviews Cancer 2012, 12.
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@article{lengauer2012d, TITLE = {Managing Drug Resistance in Cancer: {\textbraceleft}Lessons{\textbraceright} from {\textbraceleft}{HIV}{\textbraceright} Therapy}, AUTHOR = {Bock, Christoph and Lengauer, Thomas}, LANGUAGE = {eng}, ISSN = {1474-175X}, DOI = {10.1038/nrc3297}, LOCALID = {Local-ID: A03DC150927CCEB8C1257AD3004C3714-lengauer2012d}, PUBLISHER = {Nature Pub. Group}, ADDRESS = {New York, NY}, YEAR = {2012}, DATE = {2012}, JOURNAL = {Nature Reviews Cancer}, VOLUME = {12}, NUMBER = {7}, PAGES = {494--501}, }
Endnote
%0 Journal Article %A Bock, Christoph %A Lengauer, Thomas %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Managing Drug Resistance in Cancer: {Lessons} from {HIV} Therapy : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-C53D-6 %R 10.1038/nrc3297 %F OTHER: Local-ID: A03DC150927CCEB8C1257AD3004C3714-lengauer2012d %D 2012 %J Nature Reviews Cancer %O Nat. Rev. Cancer %V 12 %N 7 %& 494 %P 494 - 501 %I Nature Pub. Group %C New York, NY %@ false
183. Bock C, Lengauer T: Epigenom-Karten erstellen und nutzen. BIOspektrum 2012, 18.
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@article{BockLengauer2012b, TITLE = {{Epigenom-Karten erstellen und nutzen}}, AUTHOR = {Bock, Christoph and Lengauer, Thomas}, LANGUAGE = {deu}, ISSN = {0947-0867}, DOI = {10.1007/s12268-012-0152-5}, PUBLISHER = {Spektrum Akad. Verlag}, ADDRESS = {Heidelberg}, YEAR = {2012}, DATE = {2012}, JOURNAL = {BIOspektrum}, VOLUME = {18}, NUMBER = {2}, PAGES = {138--141}, }
Endnote
%0 Journal Article %A Bock, Christoph %A Lengauer, Thomas %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Epigenom-Karten erstellen und nutzen : %G deu %U http://hdl.handle.net/11858/00-001M-0000-0019-F6D7-6 %R 10.1007/s12268-012-0152-5 %7 2012 %D 2012 %J BIOspektrum %V 18 %N 2 %& 138 %P 138 - 141 %I Spektrum Akad. Verlag %C Heidelberg %@ false
184. Bogojeska J, Stöckel D, Zazzi M, Kaiser R, Incardona F, Rosen-Zvi M, Lengauer T: History-alignment Models for Bias-aware Prediction of Virological Response to HIV Combination Therapy. In Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS 2012). Journal of Machine Learning Research; 2012. [JMLR Workshop and Conference Proceedings]
Abstract
The relevant HIV data sets used for predicting outcomes of HIV combination therapies suffer from several problems: different treatment backgrounds of the samples, uneven representation with respect to the level of therapy experience and uneven therapy representation. Also, they comprise only viral strain(s) that can be detected in the patients� blood serum. The approach presented in this paper tackles these issues by considering not only the most recent therapies but also the different treatment backgrounds of the samples making up the clinical data sets when predicting the outcomes of HIV therapies. For this purpose, we introduce a similarity measure for sequences of therapies and use it for training separate linear models for predicting therapy outcome for each target sample. Compared to the most commonly used approach that encodes all available treatment information only by specific input features our approach has the advantage of delivering significantly more accurate predictions for therapy-experienced patients and for rare therapies. Additionally, the sample-specific models are more interpretable which is very important in medical applications.
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@inproceedings{Bogojeska2012b, TITLE = {History-alignment Models for Bias-aware Prediction of Virological Response to {HIV} Combination Therapy}, AUTHOR = {Bogojeska, Jasmina and St{\"o}ckel, Daniel and Zazzi, Maurizio and Kaiser, Rolf and Incardona, Francesca and Rosen-Zvi, Michal and Lengauer, Thomas}, LANGUAGE = {eng}, LOCALID = {Local-ID: 124D02AE50A81550C1257AD20046A1AC-Bogojeska2012b}, PUBLISHER = {Journal of Machine Learning Research}, YEAR = {2012}, DATE = {2012-04}, ABSTRACT = {The relevant HIV data sets used for predicting outcomes of HIV combination therapies suffer from several problems: different treatment backgrounds of the samples, uneven representation with respect to the level of therapy experience and uneven therapy representation. Also, they comprise only viral strain(s) that can be detected in the patients{\diamond} blood serum. The approach presented in this paper tackles these issues by considering not only the most recent therapies but also the different treatment backgrounds of the samples making up the clinical data sets when predicting the outcomes of HIV therapies. For this purpose, we introduce a similarity measure for sequences of therapies and use it for training separate linear models for predicting therapy outcome for each target sample. Compared to the most commonly used approach that encodes all available treatment information only by specific input features our approach has the advantage of delivering significantly more accurate predictions for therapy-experienced patients and for rare therapies. Additionally, the sample-specific models are more interpretable which is very important in medical applications.}, BOOKTITLE = {Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS 2012)}, EDITOR = {Lawrence, Neil and Girolami, Mark}, PAGES = {118--126}, SERIES = {JMLR Workshop and Conference Proceedings}, VOLUME = {22}, ADDRESS = {La Palma, Canary Islands, Spain}, }
Endnote
%0 Conference Proceedings %A Bogojeska, Jasmina %A Stöckel, Daniel %A Zazzi, Maurizio %A Kaiser, Rolf %A Incardona, Francesca %A Rosen-Zvi, Michal %A Lengauer, Thomas %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T History-alignment Models for Bias-aware Prediction of Virological Response to HIV Combination Therapy : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-C576-4 %F OTHER: Local-ID: 124D02AE50A81550C1257AD20046A1AC-Bogojeska2012b %D 2012 %B Fifteenth International Conference on Artificial Intelligence and Statistics %Z date of event: 2012-04-21 - 2012-04-23 %C La Palma, Canary Islands, Spain %X The relevant HIV data sets used for predicting outcomes of HIV combination therapies suffer from several problems: different treatment backgrounds of the samples, uneven representation with respect to the level of therapy experience and uneven therapy representation. Also, they comprise only viral strain(s) that can be detected in the patients� blood serum. The approach presented in this paper tackles these issues by considering not only the most recent therapies but also the different treatment backgrounds of the samples making up the clinical data sets when predicting the outcomes of HIV therapies. For this purpose, we introduce a similarity measure for sequences of therapies and use it for training separate linear models for predicting therapy outcome for each target sample. Compared to the most commonly used approach that encodes all available treatment information only by specific input features our approach has the advantage of delivering significantly more accurate predictions for therapy-experienced patients and for rare therapies. Additionally, the sample-specific models are more interpretable which is very important in medical applications. %B Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS 2012) %E Lawrence, Neil; Girolami, Mark %P 118 - 126 %I Journal of Machine Learning Research %B JMLR Workshop and Conference Proceedings %N 22
185. Bogojeska J, Lengauer T: Hierarchical Bayes Model for Predicting Effectiveness of HIV Combination Therapies. Statistical Applications in Genetics and Molecular Biology 2012, 11.
Abstract
HIV patients are treated by administration of combinations of antiretroviral drugs. The very large number of such combinations makes the manual search for an effective therapy practically impossible, especially in advanced stages of the disease. Therapy selection can be supported by statistical methods that predict the outcomes of candidate therapies. However, these methods are based on clinical data sets that have highly unbalanced therapy representation.This paper presents a novel approach that considers each drug belonging to a target combination therapy as a separate task in a multi-task hierarchical Bayes setting. The drug-specific models take into account information on all therapies containing the drug, not just the target therapy. In this way, we can circumvent the problem of data sparseness pertaining to some target therapies.The computational validation shows that compared to the most commonly used approach that provides therapy information in the form of input features, our model has significantly higher predictive power for therapies with very few training samples and is at least as powerful for abundant therapies.
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@article{Bogojeska2012a, TITLE = {Hierarchical {Bayes} Model for Predicting Effectiveness of {HIV} Combination Therapies}, AUTHOR = {Bogojeska, Jasmina and Lengauer, Thomas}, LANGUAGE = {eng}, ISSN = {1554-6115}, DOI = {10.1515/1544-6115.1769}, LOCALID = {Local-ID: 7280BD1B9F1F2D6DC1257AD200454050-Bogojeska2012a}, PUBLISHER = {De Gruyter}, ADDRESS = {Boston, MA}, YEAR = {2012}, DATE = {2012}, ABSTRACT = {HIV patients are treated by administration of combinations of antiretroviral drugs. The very large number of such combinations makes the manual search for an effective therapy practically impossible, especially in advanced stages of the disease. Therapy selection can be supported by statistical methods that predict the outcomes of candidate therapies. However, these methods are based on clinical data sets that have highly unbalanced therapy representation.This paper presents a novel approach that considers each drug belonging to a target combination therapy as a separate task in a multi-task hierarchical Bayes setting. The drug-specific models take into account information on all therapies containing the drug, not just the target therapy. In this way, we can circumvent the problem of data sparseness pertaining to some target therapies.The computational validation shows that compared to the most commonly used approach that provides therapy information in the form of input features, our model has significantly higher predictive power for therapies with very few training samples and is at least as powerful for abundant therapies.}, JOURNAL = {Statistical Applications in Genetics and Molecular Biology}, VOLUME = {11}, NUMBER = {3}, PAGES = {1--19}, EID = {11}, }
Endnote
%0 Journal Article %A Bogojeska, Jasmina %A Lengauer, Thomas %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Hierarchical Bayes Model for Predicting Effectiveness of HIV Combination Therapies : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-C580-C %R 10.1515/1544-6115.1769 %F OTHER: Local-ID: 7280BD1B9F1F2D6DC1257AD200454050-Bogojeska2012a %7 2012-04-27 %D 2012 %X HIV patients are treated by administration of combinations of antiretroviral drugs. The very large number of such combinations makes the manual search for an effective therapy practically impossible, especially in advanced stages of the disease. Therapy selection can be supported by statistical methods that predict the outcomes of candidate therapies. However, these methods are based on clinical data sets that have highly unbalanced therapy representation.This paper presents a novel approach that considers each drug belonging to a target combination therapy as a separate task in a multi-task hierarchical Bayes setting. The drug-specific models take into account information on all therapies containing the drug, not just the target therapy. In this way, we can circumvent the problem of data sparseness pertaining to some target therapies.The computational validation shows that compared to the most commonly used approach that provides therapy information in the form of input features, our model has significantly higher predictive power for therapies with very few training samples and is at least as powerful for abundant therapies. %J Statistical Applications in Genetics and Molecular Biology %V 11 %N 3 %& 1 %P 1 - 19 %Z sequence number: 11 %I De Gruyter %C Boston, MA %@ false
186. Bozek K, Eckhardt M, Sierra S, Kaiser R, Kräusslich H-G, Müller B, Lengauer T: An Expanded Model of HIV Cell Entry Phenotype Based on Multi-Parameter Single-Cell Data. Retrovirology 2012, 9.
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@article{lengauer2012e, TITLE = {An Expanded Model of {HIV} Cell Entry Phenotype Based on Multi-Parameter Single-Cell Data}, AUTHOR = {Bozek, Katarzyna and Eckhardt, Manon and Sierra, Saleta and Kaiser, Rolf and Kr{\"a}usslich, Hans-Georg and M{\"u}ller, Barbara and Lengauer, Thomas}, LANGUAGE = {eng}, ISSN = {1742-4690}, DOI = {10.1186/1742-4690-9-60}, LOCALID = {Local-ID: A43326DD97819D5BC1257AD3004C64D3-lengauer2012e}, PUBLISHER = {BioMed Central}, ADDRESS = {London}, YEAR = {2012}, JOURNAL = {Retrovirology}, VOLUME = {9}, NUMBER = {1}, PAGES = {60:1--60:15}, EID = {60}, }
Endnote
%0 Journal Article %A Bozek, Katarzyna %A Eckhardt, Manon %A Sierra, Saleta %A Kaiser, Rolf %A Kräusslich, Hans-Georg %A Müller, Barbara %A Lengauer, Thomas %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T An Expanded Model of HIV Cell Entry Phenotype Based on Multi-Parameter Single-Cell Data : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-D1E1-2 %R 10.1186/1742-4690-9-60 %F OTHER: Local-ID: A43326DD97819D5BC1257AD3004C64D3-lengauer2012e %7 2012-07-25 %D 2012 %8 25.07.2012 %J Retrovirology %V 9 %N 1 %& 60:1 %P 60:1 - 60:15 %Z sequence number: 60 %I BioMed Central %C London %@ false %U http://www.retrovirology.com/content/9/1/60
187. Calvanese V, Fernandez AF, Urdinguio RG, Suarez-Álvarez B, Mangas C, Pérez-García V, Bueno C, Montes R, Ramos-Mejía V, Martínez-Camblor P, Ferrero C, Assenov Y, Bock C, Menendez P, Carrera AC, Lopez-Larrea C, Fraga MF: A Promoter DNA Demethylation Landscape of Human Hematopoietic Differentiation. Nucleic Acids Research 2012, 40.
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@article{Calvanese2012, TITLE = {A Promoter {DNA} Demethylation Landscape of Human Hematopoietic Differentiation}, AUTHOR = {Calvanese, Vincenzo and Fernandez, Agust{\'i}n F. and Urdinguio, Roc{\'i}o G. and Suarez-{\'A}lvarez, Beatriz and Mangas, Cristina and P{\'e}rez-Garc{\'i}a, Vicente and Bueno, Clara and Montes, Rosa and Ramos-Mej{\'i}a, Ver{\'o}nica and Mart{\'i}nez-Camblor, Pablo and Ferrero, Cecilia and Assenov, Yassen and Bock, Christoph and Menendez, Pablo and Carrera, Ana Clara and Lopez-Larrea, Carlos and Fraga, Mario F.}, LANGUAGE = {eng}, DOI = {10.1093/nar/gkr685}, LOCALID = {Local-ID: 64F8D3538B0D036BC1257B02002FCC96-Calvanese2012}, PUBLISHER = {Oxford University Press}, ADDRESS = {Oxford}, YEAR = {2012}, DATE = {2012}, JOURNAL = {Nucleic Acids Research}, VOLUME = {40}, NUMBER = {1}, PAGES = {116--131}, }
Endnote
%0 Journal Article %A Calvanese, Vincenzo %A Fernandez, Agustín F. %A Urdinguio, Rocío G. %A Suarez-Álvarez, Beatriz %A Mangas, Cristina %A Pérez-García, Vicente %A Bueno, Clara %A Montes, Rosa %A Ramos-Mejía, Verónica %A Martínez-Camblor, Pablo %A Ferrero, Cecilia %A Assenov, Yassen %A Bock, Christoph %A Menendez, Pablo %A Carrera, Ana Clara %A Lopez-Larrea, Carlos %A Fraga, Mario F. %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations %T A Promoter DNA Demethylation Landscape of Human Hematopoietic Differentiation : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-BAF8-8 %R 10.1093/nar/gkr685 %F OTHER: Local-ID: 64F8D3538B0D036BC1257B02002FCC96-Calvanese2012 %7 2011-09-12 %D 2012 %J Nucleic Acids Research %V 40 %N 1 %& 116 %P 116 - 131 %I Oxford University Press %C Oxford
188. Dietzen M, Zotenko E, Hildebrandt A, Lengauer T: On the Applicability of Elastic Network Normal Modes in Small-molecule Docking. Journal of Chemical Information and Modeling 2012, 52.
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@article{Dietzen2012, TITLE = {On the Applicability of Elastic Network Normal Modes in Small-molecule Docking}, AUTHOR = {Dietzen, Matthias and Zotenko, Elena and Hildebrandt, Andreas and Lengauer, Thomas}, LANGUAGE = {eng}, ISSN = {1549-9596}, DOI = {10.1021/ci2004847}, LOCALID = {Local-ID: D958D8BAFF9537BAC1257AD3004D42CE-Dietzen2012}, PUBLISHER = {American Chemical Society}, ADDRESS = {Washington, D.C.}, YEAR = {2012}, DATE = {2012}, JOURNAL = {Journal of Chemical Information and Modeling}, VOLUME = {52}, NUMBER = {3}, PAGES = {844--856}, }
Endnote
%0 Journal Article %A Dietzen, Matthias %A Zotenko, Elena %A Hildebrandt, Andreas %A Lengauer, Thomas %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T On the Applicability of Elastic Network Normal Modes in Small-molecule Docking : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-D1D0-8 %R 10.1021/ci2004847 %F OTHER: Local-ID: D958D8BAFF9537BAC1257AD3004D42CE-Dietzen2012 %7 2012-02-10 %D 2012 %J Journal of Chemical Information and Modeling %V 52 %N 3 %& 844 %P 844 - 856 %I American Chemical Society %C Washington, D.C. %@ false
189. Doncheva NT, Kacprowski T, Albrecht M: Recent Approaches to the Prioritization of Candidate Disease Genes. WIREs Systems Biology and Medicine 2012, 4.
Abstract
Many efforts are still devoted to the discovery of genes involved with specific phenotypes, in particular, diseases. High-throughput techniques are thus applied frequently to detect dozens or even hundreds of candidate genes. However, the experimental validation of many candidates is often an expensive and time-consuming task. Therefore, a great variety of computational approaches has been developed to support the identification of the most promising candidates for follow-up studies. The biomedical knowledge already available about the disease of interest and related genes is commonly exploited to find new gene�disease associations and to prioritize candidates. In this review, we highlight recent methodological advances in this research field of candidate gene prioritization. We focus on approaches that use network information and integrate heterogeneous data sources. Furthermore, we discuss current benchmarking procedures for evaluating and comparing different prioritization methods.
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@article{Albrecht2012c, TITLE = {Recent Approaches to the Prioritization of Candidate Disease Genes}, AUTHOR = {Doncheva, Nadezhda Tsankova and Kacprowski, Tim and Albrecht, Mario}, LANGUAGE = {eng}, ISSN = {1939-005X}, DOI = {10.1002/wsbm.1177}, LOCALID = {Local-ID: 76A8D4EB252E1DA8C1257AD8005C43C5-Albrecht2012c}, PUBLISHER = {Wiley}, ADDRESS = {Chichester}, YEAR = {2012}, ABSTRACT = {Many efforts are still devoted to the discovery of genes involved with specific phenotypes, in particular, diseases. High-throughput techniques are thus applied frequently to detect dozens or even hundreds of candidate genes. However, the experimental validation of many candidates is often an expensive and time-consuming task. Therefore, a great variety of computational approaches has been developed to support the identification of the most promising candidates for follow-up studies. The biomedical knowledge already available about the disease of interest and related genes is commonly exploited to find new gene{\diamond}disease associations and to prioritize candidates. In this review, we highlight recent methodological advances in this research field of candidate gene prioritization. We focus on approaches that use network information and integrate heterogeneous data sources. Furthermore, we discuss current benchmarking procedures for evaluating and comparing different prioritization methods.}, JOURNAL = {WIREs Systems Biology and Medicine}, VOLUME = {4}, NUMBER = {5}, PAGES = {429--442}, }
Endnote
%0 Journal Article %A Doncheva, Nadezhda Tsankova %A Kacprowski, Tim %A Albrecht, Mario %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Recent Approaches to the Prioritization of Candidate Disease Genes : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-C52B-C %R 10.1002/wsbm.1177 %F OTHER: Local-ID: 76A8D4EB252E1DA8C1257AD8005C43C5-Albrecht2012c %7 2012-06-11 %D 2012 %8 11.06.2012 %X Many efforts are still devoted to the discovery of genes involved with specific phenotypes, in particular, diseases. High-throughput techniques are thus applied frequently to detect dozens or even hundreds of candidate genes. However, the experimental validation of many candidates is often an expensive and time-consuming task. Therefore, a great variety of computational approaches has been developed to support the identification of the most promising candidates for follow-up studies. The biomedical knowledge already available about the disease of interest and related genes is commonly exploited to find new gene�disease associations and to prioritize candidates. In this review, we highlight recent methodological advances in this research field of candidate gene prioritization. We focus on approaches that use network information and integrate heterogeneous data sources. Furthermore, we discuss current benchmarking procedures for evaluating and comparing different prioritization methods. %J WIREs Systems Biology and Medicine %O Wiley Interdiscip Rev Syst Biol Med Wiley Interdisciplinary Reviews: Systems Biology and Medicine %V 4 %N 5 %& 429 %P 429 - 442 %I Wiley %C Chichester %@ false
190. Doncheva NT, Assenov Y, Domingues FS, Albrecht M: Topological Analysis and Interactive Visualization of Biological Networks and Protein Structures. Nature Protocols 2012, 7.
Abstract
Computational analysis and interactive visualization of biological networks and protein structures are common tasks for gaining insight into biological processes. This protocol describes three workflows based on the NetworkAnalyzer and RINalyzer plug-ins for Cytoscape, a popular software platform for networks. NetworkAnalyzer has become a standard Cytoscape tool for comprehensive network topology analysis. In addition, RINalyzer provides methods for exploring residue interaction networks derived from protein structures. The first workflow uses NetworkAnalyzer to perform a topological analysis of biological networks. The second workflow applies RINalyzer to study protein structure and function and to compute network centrality measures. The third workflow combines NetworkAnalyzer and RINalyzer to compare residue networks. The full protocol can be completed in approximately 2 h.
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@article{Albrecht2012a, TITLE = {Topological Analysis and Interactive Visualization of Biological Networks and Protein Structures}, AUTHOR = {Doncheva, Nadezhda Tsankova and Assenov, Yassen and Domingues, Francisco S. and Albrecht, Mario}, LANGUAGE = {eng}, ISSN = {1750-2799; 1754-2189}, URL = {http://www.ncbi.nlm.nih.gov/pubmed/22422314}, DOI = {10.1038/nprot.2012.004}, LOCALID = {Local-ID: 60C74A3540567C51C1257AD4005BE1AA-Albrecht2012a}, PUBLISHER = {Nature Publishing Group}, ADDRESS = {Basingstoke}, YEAR = {2012}, DATE = {2012}, ABSTRACT = {Computational analysis and interactive visualization of biological networks and protein structures are common tasks for gaining insight into biological processes. This protocol describes three workflows based on the NetworkAnalyzer and RINalyzer plug-ins for Cytoscape, a popular software platform for networks. NetworkAnalyzer has become a standard Cytoscape tool for comprehensive network topology analysis. In addition, RINalyzer provides methods for exploring residue interaction networks derived from protein structures. The first workflow uses NetworkAnalyzer to perform a topological analysis of biological networks. The second workflow applies RINalyzer to study protein structure and function and to compute network centrality measures. The third workflow combines NetworkAnalyzer and RINalyzer to compare residue networks. The full protocol can be completed in approximately 2 h.}, JOURNAL = {Nature Protocols}, VOLUME = {7}, NUMBER = {4}, PAGES = {670--685}, }
Endnote
%0 Journal Article %A Doncheva, Nadezhda Tsankova %A Assenov, Yassen %A Domingues, Francisco S. %A Albrecht, Mario %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Topological Analysis and Interactive Visualization of Biological Networks and Protein Structures : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-C9C0-B %R 10.1038/nprot.2012.004 %U http://www.ncbi.nlm.nih.gov/pubmed/22422314 %F OTHER: Local-ID: 60C74A3540567C51C1257AD4005BE1AA-Albrecht2012a %7 2012-03-15 %D 2012 %X Computational analysis and interactive visualization of biological networks and protein structures are common tasks for gaining insight into biological processes. This protocol describes three workflows based on the NetworkAnalyzer and RINalyzer plug-ins for Cytoscape, a popular software platform for networks. NetworkAnalyzer has become a standard Cytoscape tool for comprehensive network topology analysis. In addition, RINalyzer provides methods for exploring residue interaction networks derived from protein structures. The first workflow uses NetworkAnalyzer to perform a topological analysis of biological networks. The second workflow applies RINalyzer to study protein structure and function and to compute network centrality measures. The third workflow combines NetworkAnalyzer and RINalyzer to compare residue networks. The full protocol can be completed in approximately 2 h. %K Models, Biological Protein Interaction Mapping/*methods Protein Interaction Maps Protein Structure, Tertiary Proteins/*chemistry *Software %J Nature Protocols %O Nat. Protoc. %V 7 %N 4 %& 670 %P 670 - 685 %I Nature Publishing Group %C Basingstoke %@ false
191. Eldarov N: Modeling Influenza Evolution in Response to Immune System Pressure. Universität des Saarlandes; 2012.
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@mastersthesis{EldarovMaster2012, TITLE = {Modeling Influenza Evolution in Response to Immune System Pressure}, AUTHOR = {Eldarov, Nasimi}, LANGUAGE = {eng}, LOCALID = {Local-ID: 9D5BA49656C17925C1257B270052B225-EldarovMaster2012}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2012}, DATE = {2012}, }
Endnote
%0 Thesis %A Eldarov, Nasimi %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Modeling Influenza Evolution in Response to Immune System Pressure : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-BA51-B %F OTHER: Local-ID: 9D5BA49656C17925C1257B270052B225-EldarovMaster2012 %I Universität des Saarlandes %C Saarbrücken %D 2012 %P IX, 78 p. %V master %9 master
192. Emig D, Blankenburg H, Ramírez F, Albrecht M: Functional Characterization of Human Genes from Exon Expression and RNA Interference Results. In Bioinformatics and Drug Discovery. New York, NY: Humana Press; 2012. [Methods in Molecular Biology]
Abstract
Complex biological systems comprise a large number of interacting molecules. The identification and detailed characterization of the functions of the involved genes and proteins are crucial for modeling and understanding such systems. To interrogate the various cellular processes, high-throughput techniques such as the Affymetrix Exon Array or RNA interference (RNAi) screens are powerful experimental approaches for functional genomics. However, they typically yield long gene lists that require computational methods to further analyze and functionally annotate the experimental results and to gain more insight into important molecular interactions. Here, we focus on bioinformatics software tools for the functional interpretation of exon expression data to discover alternative splicing events and their impact on gene and protein architecture, molecular networks, and pathways. We additionally demonstrate how to explore large lists of candidate genes as they also result from RNAi screens. In particular, our exemplary application studies show how to analyze the function of human genes that play a major role in human stem cells or viral infections.
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@incollection{Albrecht2012f, TITLE = {Functional Characterization of Human Genes from Exon Expression and {RNA} Interference Results}, AUTHOR = {Emig, Dorothea and Blankenburg, Hagen and Ram{\'i}rez, Fidel and Albrecht, Mario}, LANGUAGE = {eng}, ISSN = {1064-3745; 1940-6029}, ISBN = {978-1-61779-964-8; 978-1-61779-965-5}, DOI = {10.1007/978-1-61779-965-5_3}, LOCALID = {Local-ID: 9FC57E3E169AAD3CC1257AD9003CFBCA-Albrecht2012f}, PUBLISHER = {Humana Press}, ADDRESS = {New York, NY}, YEAR = {2012}, DATE = {2012}, ABSTRACT = {Complex biological systems comprise a large number of interacting molecules. The identification and detailed characterization of the functions of the involved genes and proteins are crucial for modeling and understanding such systems. To interrogate the various cellular processes, high-throughput techniques such as the Affymetrix Exon Array or RNA interference (RNAi) screens are powerful experimental approaches for functional genomics. However, they typically yield long gene lists that require computational methods to further analyze and functionally annotate the experimental results and to gain more insight into important molecular interactions. Here, we focus on bioinformatics software tools for the functional interpretation of exon expression data to discover alternative splicing events and their impact on gene and protein architecture, molecular networks, and pathways. We additionally demonstrate how to explore large lists of candidate genes as they also result from RNAi screens. In particular, our exemplary application studies show how to analyze the function of human genes that play a major role in human stem cells or viral infections.}, BOOKTITLE = {Bioinformatics and Drug Discovery}, EDITOR = {Larson, Richard S.}, PAGES = {33--53}, SERIES = {Methods in Molecular Biology}, VOLUME = {910}, }
Endnote
%0 Book Section %A Emig, Dorothea %A Blankenburg, Hagen %A Ramírez, Fidel %A Albrecht, Mario %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Functional Characterization of Human Genes from Exon Expression and RNA Interference Results : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-C529-0 %R 10.1007/978-1-61779-965-5_3 %F OTHER: Local-ID: 9FC57E3E169AAD3CC1257AD9003CFBCA-Albrecht2012f %D 2012 %X Complex biological systems comprise a large number of interacting molecules. The identification and detailed characterization of the functions of the involved genes and proteins are crucial for modeling and understanding such systems. To interrogate the various cellular processes, high-throughput techniques such as the Affymetrix Exon Array or RNA interference (RNAi) screens are powerful experimental approaches for functional genomics. However, they typically yield long gene lists that require computational methods to further analyze and functionally annotate the experimental results and to gain more insight into important molecular interactions. Here, we focus on bioinformatics software tools for the functional interpretation of exon expression data to discover alternative splicing events and their impact on gene and protein architecture, molecular networks, and pathways. We additionally demonstrate how to explore large lists of candidate genes as they also result from RNAi screens. In particular, our exemplary application studies show how to analyze the function of human genes that play a major role in human stem cells or viral infections. %B Bioinformatics and Drug Discovery %E Larson, Richard S. %P 33 - 53 %I Humana Press %C New York, NY %@ 978-1-61779-964-8 978-1-61779-965-5 %S Methods in Molecular Biology %N 910 %@ false
193. Faria D, Schlicker A, Pesquita C, Bastos H, Ferreira AEN, Albrecht M, Falcao AO: Mining GO Annotations for Improving Annotation Consistency. PLoS One 2012, 7.
Abstract
Despite the structure and objectivity provided by the Gene Ontology (GO), the annotation of proteins is a complex task that is subject to errors and inconsistencies. Electronically inferred annotations in particular are widely considered unreliable. However, given that manual curation of all GO annotations is unfeasible, it is imperative to improve the quality of electronically inferred annotations. In this work, we analyze the full GO molecular function annotation of UniProtKB proteins, and discuss some of the issues that affect their quality, focusing particularly on the lack of annotation consistency. Based on our analysis, we estimate that 64% of the UniProtKB proteins are incompletely annotated, and that inconsistent annotations affect 83% of the protein functions and at least 23% of the proteins. Additionally, we present and evaluate a data mining algorithm, based on the association rule learning methodology, for identifying implicit relationships between molecular function terms. The goal of this algorithm is to assist GO curators in updating GO and correcting and preventing inconsistent annotations. Our algorithm predicted 501 relationships with an estimated precision of 94%, whereas the basic association rule learning methodology predicted 12,352 relationships with a precision below 9%.
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@article{Albrecht2012d, TITLE = {Mining {GO} Annotations for Improving Annotation Consistency}, AUTHOR = {Faria, Daniel and Schlicker, Andreas and Pesquita, Catia and Bastos, Hugo and Ferreira, Ant{\'o}nio E. N. and Albrecht, Mario and Falcao, Andr{\'e} O.}, LANGUAGE = {eng}, ISSN = {1932-6203}, URL = {http://www.ncbi.nlm.nih.gov/pubmed/22848383}, DOI = {10.1371/journal.pone.0040519}, LOCALID = {Local-ID: 41B05E900499D8FAC1257AD900397AD0-Albrecht2012d}, PUBLISHER = {Public Library of Science}, ADDRESS = {San Francisco, CA}, YEAR = {2012}, ABSTRACT = {Despite the structure and objectivity provided by the Gene Ontology (GO), the annotation of proteins is a complex task that is subject to errors and inconsistencies. Electronically inferred annotations in particular are widely considered unreliable. However, given that manual curation of all GO annotations is unfeasible, it is imperative to improve the quality of electronically inferred annotations. In this work, we analyze the full GO molecular function annotation of UniProtKB proteins, and discuss some of the issues that affect their quality, focusing particularly on the lack of annotation consistency. Based on our analysis, we estimate that 64% of the UniProtKB proteins are incompletely annotated, and that inconsistent annotations affect 83% of the protein functions and at least 23% of the proteins. Additionally, we present and evaluate a data mining algorithm, based on the association rule learning methodology, for identifying implicit relationships between molecular function terms. The goal of this algorithm is to assist GO curators in updating GO and correcting and preventing inconsistent annotations. Our algorithm predicted 501 relationships with an estimated precision of 94%, whereas the basic association rule learning methodology predicted 12,352 relationships with a precision below 9%.}, JOURNAL = {PLoS One}, VOLUME = {7}, NUMBER = {7}, PAGES = {,1--7}, EID = {e40519}, }
Endnote
%0 Journal Article %A Faria, Daniel %A Schlicker, Andreas %A Pesquita, Catia %A Bastos, Hugo %A Ferreira, António E. N. %A Albrecht, Mario %A Falcao, André O. %+ External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T Mining GO Annotations for Improving Annotation Consistency : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-C9B0-F %2 PMC3405096 %R 10.1371/journal.pone.0040519 %U http://www.ncbi.nlm.nih.gov/pubmed/22848383 %F OTHER: Local-ID: 41B05E900499D8FAC1257AD900397AD0-Albrecht2012d %7 2012-07-25 %D 2012 %8 25.07.2012 %X Despite the structure and objectivity provided by the Gene Ontology (GO), the annotation of proteins is a complex task that is subject to errors and inconsistencies. Electronically inferred annotations in particular are widely considered unreliable. However, given that manual curation of all GO annotations is unfeasible, it is imperative to improve the quality of electronically inferred annotations. In this work, we analyze the full GO molecular function annotation of UniProtKB proteins, and discuss some of the issues that affect their quality, focusing particularly on the lack of annotation consistency. Based on our analysis, we estimate that 64% of the UniProtKB proteins are incompletely annotated, and that inconsistent annotations affect 83% of the protein functions and at least 23% of the proteins. Additionally, we present and evaluate a data mining algorithm, based on the association rule learning methodology, for identifying implicit relationships between molecular function terms. The goal of this algorithm is to assist GO curators in updating GO and correcting and preventing inconsistent annotations. Our algorithm predicted 501 relationships with an estimated precision of 94%, whereas the basic association rule learning methodology predicted 12,352 relationships with a precision below 9%. %K *Databases, Protein Molecular Sequence Annotation/*methods Sequence Analysis, Protein/*methods *Software %J PLoS One %V 7 %N 7 %& ,1 %P ,1 - 7 %Z sequence number: e40519 %I Public Library of Science %C San Francisco, CA %@ false %U http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3405096/
194. Fernandez AF, Assenov Y, Martin-Subero JI, Balint B, Siebert R, Taniguchi H, Yamamoto H, Hidalgo M, Tan A-C, Galm O, Ferrer I, Sanchez-Cespedes M, Villanueva A, Carmona J, Sanchez-Mut JV, Berdasco M, Moreno V, Capella G, Monk D, Ballestar E, Ropero S, Martinez R, Sanchez-Carbayo M, Prosper F, Agirre X, Fraga MF, Grana O, Perez-Jurado L, Mora J, Puig S, et al.: A DNA Methylation Fingerprint of 1628 Human Samples. Genome Research 2012, 22.
Abstract
Most of the studies characterizing DNA methylation patterns have been restricted to particular genomic loci in a limited number of human samples and pathological conditions. Herein, we present a compromise between an extremely comprehensive study of a human sample population with an intermediate level of resolution of CpGs at the genomic level. We obtained a DNA methylation fingerprint of 1628 human samples in which we interrogated 1505 CpG sites. The DNA methylation patterns revealed show this epigenetic mark to be critical in tissue-type definition and stemness, particularly around transcription start sites that are not within a CpG island. For disease, the generated DNA methylation fingerprints show that, during tumorigenesis, human cancer cells underwent a progressive gain of promoter CpG-island hypermethylation and a loss of CpG methylation in non-CpG-island promoters. Although transformed cells are those in which DNA methylation disruption is more obvious, we observed that other common human diseases, such as neurological and autoimmune disorders, had their own distinct DNA methylation profiles. Most importantly, we provide proof of principle that the DNA methylation fingerprints obtained might be useful for translational purposes by showing that we are able to identify the tumor type origin of cancers of unknown primary origin (CUPs). Thus, the DNA methylation patterns identified across the largest spectrum of samples, tissues, and diseases reported to date constitute a baseline for developing higher-resolution DNA methylation maps and provide important clues concerning the contribution of CpG methylation to tissue identity and its changes in the most prevalent human diseases.
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@article{AssenovGenomeRes2011, TITLE = {A {DNA} Methylation Fingerprint of 1628 Human Samples}, AUTHOR = {Fernandez, Augustin F. and Assenov, Yassen and Martin-Subero, Jose Ignacio and Balint, Balazs and Siebert, Reiner and Taniguchi, Hiroaki and Yamamoto, Hiroyuki and Hidalgo, Manuel and Tan, Aik-Choon and Galm, Oliver and Ferrer, Isidre and Sanchez-Cespedes, Montse and Villanueva, Alberto and Carmona, Javier and Sanchez-Mut, Jose V. and Berdasco, Maria and Moreno, Victor and Capella, Gabriel and Monk, David and Ballestar, Esteban and Ropero, Santiago and Martinez, Ramon and Sanchez-Carbayo, Marta and Prosper, Felipe and Agirre, Xabier and Fraga, Mario F. and Grana, Osvaldo and Perez-Jurado, Luis and Mora, Jaume and Puig, Susana and Prat, Jaime and Badimon, Lina and Puca, Annibale A. and Meltzer, Stephen J. and Lengauer, Thomas and Bridgewater, John and Bock, Christoph and Esteller, Manel}, LANGUAGE = {eng}, ISSN = {1088-9051}, DOI = {10.1101/gr.119867.110}, LOCALID = {Local-ID: 1D85A05983450545C125798F003F831C-AssenovGenomeRes2011}, PUBLISHER = {Cold Spring Harbor Laboratory Press}, ADDRESS = {Cold Spring Harbor, N.Y.}, YEAR = {2012}, DATE = {2012}, ABSTRACT = {Most of the studies characterizing DNA methylation patterns have been restricted to particular genomic loci in a limited number of human samples and pathological conditions. Herein, we present a compromise between an extremely comprehensive study of a human sample population with an intermediate level of resolution of CpGs at the genomic level. We obtained a DNA methylation fingerprint of 1628 human samples in which we interrogated 1505 CpG sites. The DNA methylation patterns revealed show this epigenetic mark to be critical in tissue-type definition and stemness, particularly around transcription start sites that are not within a CpG island. For disease, the generated DNA methylation fingerprints show that, during tumorigenesis, human cancer cells underwent a progressive gain of promoter CpG-island hypermethylation and a loss of CpG methylation in non-CpG-island promoters. Although transformed cells are those in which DNA methylation disruption is more obvious, we observed that other common human diseases, such as neurological and autoimmune disorders, had their own distinct DNA methylation profiles. Most importantly, we provide proof of principle that the DNA methylation fingerprints obtained might be useful for translational purposes by showing that we are able to identify the tumor type origin of cancers of unknown primary origin (CUPs). Thus, the DNA methylation patterns identified across the largest spectrum of samples, tissues, and diseases reported to date constitute a baseline for developing higher-resolution DNA methylation maps and provide important clues concerning the contribution of CpG methylation to tissue identity and its changes in the most prevalent human diseases.}, JOURNAL = {Genome Research}, VOLUME = {22}, NUMBER = {2}, PAGES = {407--419}, }
Endnote
%0 Journal Article %A Fernandez, Augustin F. %A Assenov, Yassen %A Martin-Subero, Jose Ignacio %A Balint, Balazs %A Siebert, Reiner %A Taniguchi, Hiroaki %A Yamamoto, Hiroyuki %A Hidalgo, Manuel %A Tan, Aik-Choon %A Galm, Oliver %A Ferrer, Isidre %A Sanchez-Cespedes, Montse %A Villanueva, Alberto %A Carmona, Javier %A Sanchez-Mut, Jose V. %A Berdasco, Maria %A Moreno, Victor %A Capella, Gabriel %A Monk, David %A Ballestar, Esteban %A Ropero, Santiago %A Martinez, Ramon %A Sanchez-Carbayo, Marta %A Prosper, Felipe %A Agirre, Xabier %A Fraga, Mario F. %A Grana, Osvaldo %A Perez-Jurado, Luis %A Mora, Jaume %A Puig, Susana %A Prat, Jaime %A Badimon, Lina %A Puca, Annibale A. %A Meltzer, Stephen J. %A Lengauer, Thomas %A Bridgewater, John %A Bock, Christoph %A Esteller, Manel %+ External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T A DNA Methylation Fingerprint of 1628 Human Samples : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-C9A2-D %2 PMC3266047 %R 10.1101/gr.119867.110 %F OTHER: Local-ID: 1D85A05983450545C125798F003F831C-AssenovGenomeRes2011 %7 2011-05-25 %D 2012 %X Most of the studies characterizing DNA methylation patterns have been restricted to particular genomic loci in a limited number of human samples and pathological conditions. Herein, we present a compromise between an extremely comprehensive study of a human sample population with an intermediate level of resolution of CpGs at the genomic level. We obtained a DNA methylation fingerprint of 1628 human samples in which we interrogated 1505 CpG sites. The DNA methylation patterns revealed show this epigenetic mark to be critical in tissue-type definition and stemness, particularly around transcription start sites that are not within a CpG island. For disease, the generated DNA methylation fingerprints show that, during tumorigenesis, human cancer cells underwent a progressive gain of promoter CpG-island hypermethylation and a loss of CpG methylation in non-CpG-island promoters. Although transformed cells are those in which DNA methylation disruption is more obvious, we observed that other common human diseases, such as neurological and autoimmune disorders, had their own distinct DNA methylation profiles. Most importantly, we provide proof of principle that the DNA methylation fingerprints obtained might be useful for translational purposes by showing that we are able to identify the tumor type origin of cancers of unknown primary origin (CUPs). Thus, the DNA methylation patterns identified across the largest spectrum of samples, tissues, and diseases reported to date constitute a baseline for developing higher-resolution DNA methylation maps and provide important clues concerning the contribution of CpG methylation to tissue identity and its changes in the most prevalent human diseases. %K Cell Line Cell Transformation, Neoplastic/genetics Cluster Analysis CpG Islands *DNA Methylation Epigenomics/methods Gene Expression Profiling Gene Expression Regulation Humans Neoplasms/genetics %J Genome Research %V 22 %N 2 %& 407 %P 407 - 419 %I Cold Spring Harbor Laboratory Press %C Cold Spring Harbor, N.Y. %@ false %U http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3266047/
195. Feuerbach L, Halachev K, Assenov Y, Müller F, Bock C, Lengauer T: Analyzing Epigenome Data in Context of Genome Evolution and Human Diseases. In Evolutionary Genomics. Volume 2. Totowa, NJ: Humana Press; 2012. [Methods in Molecular Biology]
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@incollection{lengauer2012b, TITLE = {Analyzing Epigenome Data in Context of Genome Evolution and Human Diseases}, AUTHOR = {Feuerbach, Lars and Halachev, Konstantin and Assenov, Yassen and M{\"u}ller, Fabian and Bock, Christoph and Lengauer, Thomas}, LANGUAGE = {eng}, ISBN = {978-1-61779-584-8; 978-1-61779-585-5}, DOI = {10.1007/978-1-61779-585-5_18}, LOCALID = {Local-ID: 54748B8D02398C66C1257AD300336A25-lengauer2012b}, PUBLISHER = {Humana Press}, ADDRESS = {Totowa, NJ}, YEAR = {2012}, DATE = {2012}, BOOKTITLE = {Evolutionary Genomics}, EDITOR = {Anisimova, Maria}, VOLUME = {2}, PAGES = {431--467}, EID = {18}, SERIES = {Methods in Molecular Biology}, VOLUME = {856}, }
Endnote
%0 Book Section %A Feuerbach, Lars %A Halachev, Konstantin %A Assenov, Yassen %A Müller, Fabian %A Bock, Christoph %A Lengauer, Thomas %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Analyzing Epigenome Data in Context of Genome Evolution and Human Diseases : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-C548-C %R 10.1007/978-1-61779-585-5_18 %F OTHER: Local-ID: 54748B8D02398C66C1257AD300336A25-lengauer2012b %D 2012 %B Evolutionary Genomics %E Anisimova, Maria %V 2 %P 431 - 467 %& 18 %I Humana Press %C Totowa, NJ %@ 978-1-61779-584-8 978-1-61779-585-5 %S Methods in Molecular Biology %N 856
196. Garai A, Zeke A, Gógl G, Töro I, Fördos F, Blankenburg H, Bárkai T, Varga J, Alexa A, Emig D, Albrecht M, Reményi A: Specificity of Linear Motifs that Bind to a Common Mitogen-activated Protein Kinase Docking Groove. Science Signaling 2012, 5.
Abstract
Mitogen-activated protein kinases (MAPKs) have a docking groove that interacts with linear "docking" motifs in binding partners. To determine the structural basis of binding specificity between MAPKs and docking motifs, we quantitatively analyzed the ability of 15 docking motifs from diverse MAPK partners to bind to c-Jun amino-terminal kinase 1 (JNK1), p38α, and extracellular signal�regulated kinase 2 (ERK2). Classical docking motifs mediated highly specific binding only to JNK1, and only those motifs with a sequence pattern distinct from the classical MAPK binding docking motif consensus differentiated between the topographically similar docking grooves of ERK and p38α. Crystal structures of four complexes of MAPKs with docking peptides, representing JNK-specific, ERK-specific, or ERK- and p38-selective binding modes, revealed that the regions located between consensus positions in the docking motifs showed conformational diversity. Although the consensus positions in the docking motifs served as anchor points that bound to common MAPK surface features and mostly contributed to docking in a nondiscriminatory fashion, the conformation of the intervening region between the anchor points mostly determined specificity. We designed peptides with tailored MAPK binding profiles by rationally changing the length and amino acid composition of intervening regions located between anchor points. These results suggest a coherent structural model for MAPK docking specificity that reveals how short linear motifs binding to a common kinase docking groove can mediate diverse interaction patterns and contribute to correct MAPK partner selection in signaling networks.
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@article{Albrecht2012e, TITLE = {Specificity of Linear Motifs that Bind to a Common Mitogen-activated Protein Kinase Docking Groove}, AUTHOR = {Garai, Agnes and Zeke, Andr{\'a}s and G{\'o}gl, Gergo and T{\"o}ro, Imre and F{\"o}rdos, Ferenc and Blankenburg, Hagen and B{\'a}rkai, T{\"u}nde and Varga, J{\'a}nos and Alexa, Anita and Emig, Dorothea and Albrecht, Mario and Rem{\'e}nyi, Attila}, LANGUAGE = {eng}, ISSN = {1937-9145}, DOI = {10.1126/scisignal.2003004}, PUBLISHER = {AAAS}, ADDRESS = {Washington, DC}, YEAR = {2012}, ABSTRACT = {Mitogen-activated protein kinases (MAPKs) have a docking groove that interacts with linear "docking" motifs in binding partners. To determine the structural basis of binding specificity between MAPKs and docking motifs, we quantitatively analyzed the ability of 15 docking motifs from diverse MAPK partners to bind to c-Jun amino-terminal kinase 1 (JNK1), p38$\alpha$, and extracellular signal{\diamond}regulated kinase 2 (ERK2). Classical docking motifs mediated highly specific binding only to JNK1, and only those motifs with a sequence pattern distinct from the classical MAPK binding docking motif consensus differentiated between the topographically similar docking grooves of ERK and p38$\alpha$. Crystal structures of four complexes of MAPKs with docking peptides, representing JNK-specific, ERK-specific, or ERK- and p38-selective binding modes, revealed that the regions located between consensus positions in the docking motifs showed conformational diversity. Although the consensus positions in the docking motifs served as anchor points that bound to common MAPK surface features and mostly contributed to docking in a nondiscriminatory fashion, the conformation of the intervening region between the anchor points mostly determined specificity. We designed peptides with tailored MAPK binding profiles by rationally changing the length and amino acid composition of intervening regions located between anchor points. These results suggest a coherent structural model for MAPK docking specificity that reveals how short linear motifs binding to a common kinase docking groove can mediate diverse interaction patterns and contribute to correct MAPK partner selection in signaling networks.}, JOURNAL = {Science Signaling}, VOLUME = {5}, NUMBER = {245}, PAGES = {ra74,1--ra74,14}, }
Endnote
%0 Journal Article %A Garai, Agnes %A Zeke, András %A Gógl, Gergo %A Töro, Imre %A Fördos, Ferenc %A Blankenburg, Hagen %A Bárkai, Tünde %A Varga, János %A Alexa, Anita %A Emig, Dorothea %A Albrecht, Mario %A Reményi, Attila %+ External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T Specificity of Linear Motifs that Bind to a Common Mitogen-activated Protein Kinase Docking Groove : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0019-F693-B %R 10.1126/scisignal.2003004 %7 2012-10-09 %D 2012 %8 09.10.2012 %X Mitogen-activated protein kinases (MAPKs) have a docking groove that interacts with linear "docking" motifs in binding partners. To determine the structural basis of binding specificity between MAPKs and docking motifs, we quantitatively analyzed the ability of 15 docking motifs from diverse MAPK partners to bind to c-Jun amino-terminal kinase 1 (JNK1), p38α, and extracellular signal�regulated kinase 2 (ERK2). Classical docking motifs mediated highly specific binding only to JNK1, and only those motifs with a sequence pattern distinct from the classical MAPK binding docking motif consensus differentiated between the topographically similar docking grooves of ERK and p38α. Crystal structures of four complexes of MAPKs with docking peptides, representing JNK-specific, ERK-specific, or ERK- and p38-selective binding modes, revealed that the regions located between consensus positions in the docking motifs showed conformational diversity. Although the consensus positions in the docking motifs served as anchor points that bound to common MAPK surface features and mostly contributed to docking in a nondiscriminatory fashion, the conformation of the intervening region between the anchor points mostly determined specificity. We designed peptides with tailored MAPK binding profiles by rationally changing the length and amino acid composition of intervening regions located between anchor points. These results suggest a coherent structural model for MAPK docking specificity that reveals how short linear motifs binding to a common kinase docking groove can mediate diverse interaction patterns and contribute to correct MAPK partner selection in signaling networks. %J Science Signaling %V 5 %N 245 %& ra74,1 %P ra74,1 - ra74,14 %I AAAS %C Washington, DC %@ false
197. Halachev K, Bast H, Albrecht F, Lengauer T, Bock C: EpiExplorer: Live Exploration and Global Analysis of Large Epigenomic Datasets. Genome Biology 2012, 13.
Abstract
ABSTRACT: Epigenome mapping consortia are generating resources of tremendous value for studying epigenetic regulation. To maximize their utility and impact, new tools are needed that facilitate interactive analysis of epigenome datasets. Here we describe EpiExplorer, a web tool for exploring genome and epigenome data on a genomic scale. We demonstrate EpiExplorer's utility by describing a hypothesis-generating analysis of DNA hydroxymethylation in relation to public reference maps of the human epigenome. All EpiExplorer analyses are performed dynamically within seconds, using an efficient and versatile text indexing scheme that we introduce to bioinformatics. EpiExplorer is available at http://epiexplorer.mpi-inf.mpg.de.
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@article{BockLengauer2012a, TITLE = {{EpiExplorer}: {Live} Exploration and Global Analysis of Large Epigenomic Datasets}, AUTHOR = {Halachev, Konstantin and Bast, Hannah and Albrecht, Felipe and Lengauer, Thomas and Bock, Christoph}, LANGUAGE = {eng}, ISSN = {1465-6906}, URL = {http://www.ncbi.nlm.nih.gov/pubmed/23034089}, DOI = {10.1186/gb-2012-13-10-r96}, LOCALID = {Local-ID: 15A6C3BF892187C2C1257AED003FCD73-BockLengauer2012a}, PUBLISHER = {BioMed Central Ltd.}, ADDRESS = {London}, YEAR = {2012}, ABSTRACT = {ABSTRACT: Epigenome mapping consortia are generating resources of tremendous value for studying epigenetic regulation. To maximize their utility and impact, new tools are needed that facilitate interactive analysis of epigenome datasets. Here we describe EpiExplorer, a web tool for exploring genome and epigenome data on a genomic scale. We demonstrate EpiExplorer's utility by describing a hypothesis-generating analysis of DNA hydroxymethylation in relation to public reference maps of the human epigenome. All EpiExplorer analyses are performed dynamically within seconds, using an efficient and versatile text indexing scheme that we introduce to bioinformatics. EpiExplorer is available at http://epiexplorer.mpi-inf.mpg.de.}, JOURNAL = {Genome Biology}, VOLUME = {13}, NUMBER = {10}, PAGES = {1--14}, EID = {R96}, }
Endnote
%0 Journal Article %A Halachev, Konstantin %A Bast, Hannah %A Albrecht, Felipe %A Lengauer, Thomas %A Bock, Christoph %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T EpiExplorer: Live Exploration and Global Analysis of Large Epigenomic Datasets : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-C951-3 %R 10.1186/gb-2012-13-10-r96 %U http://www.ncbi.nlm.nih.gov/pubmed/23034089 %F OTHER: Local-ID: 15A6C3BF892187C2C1257AED003FCD73-BockLengauer2012a %7 2012 %D 2012 %X ABSTRACT: Epigenome mapping consortia are generating resources of tremendous value for studying epigenetic regulation. To maximize their utility and impact, new tools are needed that facilitate interactive analysis of epigenome datasets. Here we describe EpiExplorer, a web tool for exploring genome and epigenome data on a genomic scale. We demonstrate EpiExplorer's utility by describing a hypothesis-generating analysis of DNA hydroxymethylation in relation to public reference maps of the human epigenome. All EpiExplorer analyses are performed dynamically within seconds, using an efficient and versatile text indexing scheme that we introduce to bioinformatics. EpiExplorer is available at http://epiexplorer.mpi-inf.mpg.de. %J Genome Biology %V 13 %N 10 %& 1 %P 1 - 14 %Z sequence number: R96 %I BioMed Central Ltd. %C London %@ false %U http://genomebiology.com/2012/13/10/R96
198. Hauschild A-C, Baumbach JI, Baumbach J: Integrated Statistical Learning of Metabolic Ion Mobility Spectrometry Profiles for Pulmonary Disease Identification. Genetics and Molecular Research 2012, 11.
Abstract
Exhaled air carries information on human health status. Ion mobility spectrometers combined with a multi-capillary column (MCC/IMS) is a well-known technology for detecting volatile organic compounds (VOCs) within human breath. This technique is relatively inexpensive, robust and easy to use in every day practice. However, the potential of this methodology depends on successful application of computational approaches for finding relevant VOCs and classification of patients into disease-specific profile groups based on the detected VOCs. We developed an integrated state-of-the-art system using sophisticated statistical learning techniques for VOC-based feature selection and supervised classification into patient groups. We analyzed breath data from 84 volunteers, each of them either suffering from chronic obstructive pulmonary disease (COPD), or both COPD and bronchial carcinoma (COPD + BC), as well as from 35 healthy volunteers, comprising a control group (CG). We standardized and integrated several statistical learning methods to provide a broad overview of their potential for distinguishing the patient groups. We found that there is strong potential for separating MCC/IMS chromatograms of healthy controls and COPD patients (best accuracy COPD vs CG: 94). However, further examination of the impact of bronchial carcinoma on COPD/no-COPD classification performance is necessary (best accuracy CG vs COPD vs COPD + BC: 79). We also extracted 20 high-scoring VOCs that allowed differentiating COPD patients from healthy controls. We conclude that these statistical learning methods have a generally high accuracy when applied to wellstructured, medical MCC/IMS data.
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BibTeX
@article{Hauschild2012, TITLE = {Integrated Statistical Learning of Metabolic Ion Mobility Spectrometry Profiles for Pulmonary Disease Identification}, AUTHOR = {Hauschild, Anne-Christin and Baumbach, J{\"o}rg Ingo and Baumbach, Jan}, LANGUAGE = {eng}, ISSN = {1676-5680}, DOI = {10.4238/2012.July.10.17}, LOCALID = {Local-ID: A68C037B14AE615DC1257AF500554A14-Hauschild2012}, PUBLISHER = {FUNPEC}, ADDRESS = {Ribeirao Preto, SP, Brasil}, YEAR = {2012}, ABSTRACT = {Exhaled air carries information on human health status. Ion mobility spectrometers combined with a multi-capillary column (MCC/IMS) is a well-known technology for detecting volatile organic compounds (VOCs) within human breath. This technique is relatively inexpensive, robust and easy to use in every day practice. However, the potential of this methodology depends on successful application of computational approaches for finding relevant VOCs and classification of patients into disease-specific profile groups based on the detected VOCs. We developed an integrated state-of-the-art system using sophisticated statistical learning techniques for VOC-based feature selection and supervised classification into patient groups. We analyzed breath data from 84 volunteers, each of them either suffering from chronic obstructive pulmonary disease (COPD), or both COPD and bronchial carcinoma (COPD + BC), as well as from 35 healthy volunteers, comprising a control group (CG). We standardized and integrated several statistical learning methods to provide a broad overview of their potential for distinguishing the patient groups. We found that there is strong potential for separating MCC/IMS chromatograms of healthy controls and COPD patients (best accuracy COPD vs CG: 94). However, further examination of the impact of bronchial carcinoma on COPD/no-COPD classification performance is necessary (best accuracy CG vs COPD vs COPD + BC: 79). We also extracted 20 high-scoring VOCs that allowed differentiating COPD patients from healthy controls. We conclude that these statistical learning methods have a generally high accuracy when applied to wellstructured, medical MCC/IMS data.}, JOURNAL = {Genetics and Molecular Research}, VOLUME = {11}, NUMBER = {3}, PAGES = {2733--2744}, }
Endnote
%0 Journal Article %A Hauschild, Anne-Christin %A Baumbach, Jörg Ingo %A Baumbach, Jan %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Integrated Statistical Learning of Metabolic Ion Mobility Spectrometry Profiles for Pulmonary Disease Identification : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-BB12-4 %R 10.4238/2012.July.10.17 %F OTHER: Local-ID: A68C037B14AE615DC1257AF500554A14-Hauschild2012 %7 2012-07-10 %D 2012 %8 10.07.2012 %X Exhaled air carries information on human health status. Ion mobility spectrometers combined with a multi-capillary column (MCC/IMS) is a well-known technology for detecting volatile organic compounds (VOCs) within human breath. This technique is relatively inexpensive, robust and easy to use in every day practice. However, the potential of this methodology depends on successful application of computational approaches for finding relevant VOCs and classification of patients into disease-specific profile groups based on the detected VOCs. We developed an integrated state-of-the-art system using sophisticated statistical learning techniques for VOC-based feature selection and supervised classification into patient groups. We analyzed breath data from 84 volunteers, each of them either suffering from chronic obstructive pulmonary disease (COPD), or both COPD and bronchial carcinoma (COPD + BC), as well as from 35 healthy volunteers, comprising a control group (CG). We standardized and integrated several statistical learning methods to provide a broad overview of their potential for distinguishing the patient groups. We found that there is strong potential for separating MCC/IMS chromatograms of healthy controls and COPD patients (best accuracy COPD vs CG: 94). However, further examination of the impact of bronchial carcinoma on COPD/no-COPD classification performance is necessary (best accuracy CG vs COPD vs COPD + BC: 79). We also extracted 20 high-scoring VOCs that allowed differentiating COPD patients from healthy controls. We conclude that these statistical learning methods have a generally high accuracy when applied to wellstructured, medical MCC/IMS data. %J Genetics and Molecular Research %V 11 %N 3 %& 2733 %P 2733 - 2744 %I FUNPEC %C Ribeirao Preto, SP, Brasil %@ false %U http://dx.doi.org/10.4238/2012.July.10.17
199. Hauschild A-C, Schneider T, Pauling J, Rupp K, Jang M, Baumbach JI, Baumbach J: Computational Methods for Metabolomic Data Analysis of Ion Mobility Spectrometry Data - Reviewing the State of the Art. Metabolites 2012, 2.
Abstract
Ion mobility spectrometry combined with multi-capillary columns (MCC/IMS) is a well known technology for detecting volatile organic compounds (VOCs). We may utilize MCC/IMS for scanning human exhaled air, bacterial colonies or cell lines, for example. Thereby we gain information about the human health status or infection threats. We may further study the metabolic response of living cells to external perturbations. The instrument is comparably cheap, robust and easy to use in every day practice. However, the potential of the MCC/IMS methodology depends on the successful application of computational approaches for analyzing the huge amount of emerging data sets. Here, we will review the state of the art and highlight existing challenges. First, we address methods for raw data handling, data storage and visualization. Afterwards we will introduce de-noising, peak picking and other pre-processing approaches. We will discuss statistical methods for analyzing correlations between peaks and diseases or medical treatment. Finally, we study up-to-date machine learning techniques for identifying robust biomarker molecules that allow classifying patients into healthy and diseased groups. We conclude that MCC/IMS coupled with sophisticated computational methods has the potential to successfully address a broad range of biomedical questions. While we can solve most of the data pre-processing steps satisfactorily, some computational challenges with statistical learning and model validation remain.
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@article{Hauschild2012b, TITLE = {Computational Methods for Metabolomic Data Analysis of Ion Mobility Spectrometry Data -- Reviewing the State of the Art}, AUTHOR = {Hauschild, Anne-Christin and Schneider, Till and Pauling, Josch and Rupp, Kathrin and Jang, Mi and Baumbach, J{\"o}rg Ingo and Baumbach, Jan}, LANGUAGE = {eng}, ISBN = {2218-1989}, DOI = {10.3390/metabo2040733}, PUBLISHER = {MDPI}, ADDRESS = {Basel}, YEAR = {2012}, DATE = {2012}, ABSTRACT = {Ion mobility spectrometry combined with multi-capillary columns (MCC/IMS) is a well known technology for detecting volatile organic compounds (VOCs). We may utilize MCC/IMS for scanning human exhaled air, bacterial colonies or cell lines, for example. Thereby we gain information about the human health status or infection threats. We may further study the metabolic response of living cells to external perturbations. The instrument is comparably cheap, robust and easy to use in every day practice. However, the potential of the MCC/IMS methodology depends on the successful application of computational approaches for analyzing the huge amount of emerging data sets. Here, we will review the state of the art and highlight existing challenges. First, we address methods for raw data handling, data storage and visualization. Afterwards we will introduce de-noising, peak picking and other pre-processing approaches. We will discuss statistical methods for analyzing correlations between peaks and diseases or medical treatment. Finally, we study up-to-date machine learning techniques for identifying robust biomarker molecules that allow classifying patients into healthy and diseased groups. We conclude that MCC/IMS coupled with sophisticated computational methods has the potential to successfully address a broad range of biomedical questions. While we can solve most of the data pre-processing steps satisfactorily, some computational challenges with statistical learning and model validation remain.}, JOURNAL = {Metabolites}, VOLUME = {2}, PAGES = {733--755}, }
Endnote
%0 Journal Article %A Hauschild, Anne-Christin %A Schneider, Till %A Pauling, Josch %A Rupp, Kathrin %A Jang, Mi %A Baumbach, Jörg Ingo %A Baumbach, Jan %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Computational Methods for Metabolomic Data Analysis of Ion Mobility Spectrometry Data - Reviewing the State of the Art : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0019-F4A8-D %@ 2218-1989 %R 10.3390/metabo2040733 %D 2012 %X Ion mobility spectrometry combined with multi-capillary columns (MCC/IMS) is a well known technology for detecting volatile organic compounds (VOCs). We may utilize MCC/IMS for scanning human exhaled air, bacterial colonies or cell lines, for example. Thereby we gain information about the human health status or infection threats. We may further study the metabolic response of living cells to external perturbations. The instrument is comparably cheap, robust and easy to use in every day practice. However, the potential of the MCC/IMS methodology depends on the successful application of computational approaches for analyzing the huge amount of emerging data sets. Here, we will review the state of the art and highlight existing challenges. First, we address methods for raw data handling, data storage and visualization. Afterwards we will introduce de-noising, peak picking and other pre-processing approaches. We will discuss statistical methods for analyzing correlations between peaks and diseases or medical treatment. Finally, we study up-to-date machine learning techniques for identifying robust biomarker molecules that allow classifying patients into healthy and diseased groups. We conclude that MCC/IMS coupled with sophisticated computational methods has the potential to successfully address a broad range of biomedical questions. While we can solve most of the data pre-processing steps satisfactorily, some computational challenges with statistical learning and model validation remain. %J Metabolites %V 2 %& 733 %P 733 - 755 %I MDPI %C Basel
200. Heger E, Thielen A, Gilles R, Obermeier M, Lengauer T, Kaiser R, Trapp S: APOBEC3G/F as one Possible Driving Force for Co-receptor Switch of the Human Immunodeficiency Virus-1. Medical Microbiology and Immunology 2012, 201.
Abstract
Human immunodeficiency virus-1 tropism highly correlates with the amino acid (aa) composition of the third hypervariable region (V3) of gp120. A shift towards more positively charged aa is seen when binding to CXCR4 compared with CCR5 (X4 vs. R5 strains), especially positions 11 and 25 (11/25-rule) predicting X4 viruses in the presence of positively charged residues. At nucleotide levels, negatively or uncharged aa, e.g., aspartic and glutamic acid and glycine, which are encoded by the triplets GAN (guanine-adenosine-any nucleotide) or GGN are found more often in R5 strains. Positively charged aa such as arginine and lysine encoded by AAR or AGR (CGN) (R means A or G) are seen more frequently in X4 strains suggesting our hypothesis that a switch from R5 to X4 strains occurs via a G-to-A mutation. 1527 V3 sequences from three independent data sets of X4 and R5 strains were analysed with respect to their triplet composition. A higher number of G-containing triplets was found in R5 viruses, whereas X4 strains displayed a higher content of A-comprising triplets. These findings also support our hypothesis that G-to-A mutations are leading to the co-receptor switch from R5 to X4 strains. Causative agents for G-to-A mutations are the deaminases APOBEC3F and APOBEC3G. We therefore hypothesize that these proteins are one driving force facilitating the appearance of X4 variants. G-to-A mutations can lead to a switch from negatively to positively charged aa and a respective alteration of the net charge of gp120 resulting in a change of co-receptor usage.
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@article{lengauer2012a, TITLE = {{APOBEC3G/F} as one Possible Driving Force for Co-receptor Switch of the Human Immunodeficiency Virus-1}, AUTHOR = {Heger, Eva and Thielen, Alexander and Gilles, Ramona and Obermeier, Martin and Lengauer, Thomas and Kaiser, Rolf and Trapp, Susanna}, LANGUAGE = {eng}, ISSN = {0300-8584}, DOI = {10.1007/s00430-011-0199-9}, LOCALID = {Local-ID: E2CADF8149F99CFEC1257AD30032E02E-lengauer2012a}, PUBLISHER = {Springer}, ADDRESS = {New York, NY}, YEAR = {2012}, DATE = {2012}, ABSTRACT = {Human immunodeficiency virus-1 tropism highly correlates with the amino acid (aa) composition of the third hypervariable region (V3) of gp120. A shift towards more positively charged aa is seen when binding to CXCR4 compared with CCR5 (X4 vs. R5 strains), especially positions 11 and 25 (11/25-rule) predicting X4 viruses in the presence of positively charged residues. At nucleotide levels, negatively or uncharged aa, e.g., aspartic and glutamic acid and glycine, which are encoded by the triplets GAN (guanine-adenosine-any nucleotide) or GGN are found more often in R5 strains. Positively charged aa such as arginine and lysine encoded by AAR or AGR (CGN) (R means A or G) are seen more frequently in X4 strains suggesting our hypothesis that a switch from R5 to X4 strains occurs via a G-to-A mutation. 1527 V3 sequences from three independent data sets of X4 and R5 strains were analysed with respect to their triplet composition. A higher number of G-containing triplets was found in R5 viruses, whereas X4 strains displayed a higher content of A-comprising triplets. These findings also support our hypothesis that G-to-A mutations are leading to the co-receptor switch from R5 to X4 strains. Causative agents for G-to-A mutations are the deaminases APOBEC3F and APOBEC3G. We therefore hypothesize that these proteins are one driving force facilitating the appearance of X4 variants. G-to-A mutations can lead to a switch from negatively to positively charged aa and a respective alteration of the net charge of gp120 resulting in a change of co-receptor usage.}, JOURNAL = {Medical Microbiology and Immunology}, VOLUME = {201}, NUMBER = {1}, PAGES = {7--16}, }
Endnote
%0 Journal Article %A Heger, Eva %A Thielen, Alexander %A Gilles, Ramona %A Obermeier, Martin %A Lengauer, Thomas %A Kaiser, Rolf %A Trapp, Susanna %+ External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations %T APOBEC3G/F as one Possible Driving Force for Co-receptor Switch of the Human Immunodeficiency Virus-1 : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-C901-A %R 10.1007/s00430-011-0199-9 %F OTHER: Local-ID: E2CADF8149F99CFEC1257AD30032E02E-lengauer2012a %7 2011-05-15 %D 2012 %X Human immunodeficiency virus-1 tropism highly correlates with the amino acid (aa) composition of the third hypervariable region (V3) of gp120. A shift towards more positively charged aa is seen when binding to CXCR4 compared with CCR5 (X4 vs. R5 strains), especially positions 11 and 25 (11/25-rule) predicting X4 viruses in the presence of positively charged residues. At nucleotide levels, negatively or uncharged aa, e.g., aspartic and glutamic acid and glycine, which are encoded by the triplets GAN (guanine-adenosine-any nucleotide) or GGN are found more often in R5 strains. Positively charged aa such as arginine and lysine encoded by AAR or AGR (CGN) (R means A or G) are seen more frequently in X4 strains suggesting our hypothesis that a switch from R5 to X4 strains occurs via a G-to-A mutation. 1527 V3 sequences from three independent data sets of X4 and R5 strains were analysed with respect to their triplet composition. A higher number of G-containing triplets was found in R5 viruses, whereas X4 strains displayed a higher content of A-comprising triplets. These findings also support our hypothesis that G-to-A mutations are leading to the co-receptor switch from R5 to X4 strains. Causative agents for G-to-A mutations are the deaminases APOBEC3F and APOBEC3G. We therefore hypothesize that these proteins are one driving force facilitating the appearance of X4 variants. G-to-A mutations can lead to a switch from negatively to positively charged aa and a respective alteration of the net charge of gp120 resulting in a change of co-receptor usage. %K Amino Acid Sequence Cytidine Deaminase/*metabolism Cytosine Deaminase/*metabolism HIV Envelope Protein gp120/*chemistry/genetics/*metabolism HIV Infections/virology HIV-1/*metabolism/pathogenicity Humans Molecular Sequence Data *Mutation Peptide Fragments/*chemistry/genetics/*metabolism Phenotype Polymerase Chain Reaction/methods Receptors, CCR5/genetics/*metabolism Receptors, CXCR4/genetics/*metabolism Sequence Alignment %J Medical Microbiology and Immunology %O Med. Microbiol. Immunol. %V 201 %N 1 %& 7 %P 7 - 16 %I Springer %C New York, NY %@ false
201. Kalaghatgi P: A Phylodynamic Study of HIV Transmission Networks in Europe. Universität des Saarlandes; 2012.
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@mastersthesis{Kalaghatgi2012MastersThesis, TITLE = {A Phylodynamic Study of {HIV} Transmission Networks in {E}urope}, AUTHOR = {Kalaghatgi, Prabhav}, LANGUAGE = {eng}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2012}, DATE = {2012}, }
Endnote
%0 Thesis %A Kalaghatgi, Prabhav %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T A Phylodynamic Study of HIV Transmission Networks in Europe : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-6F20-5 %I Universität des Saarlandes %C Saarbrücken %D 2012 %V master %9 master
202. Kalaghatgi P, Lawyer G: A Pan-European Phylodynamic Study of HIV-1 Transmission Networks. European Conference on Computational Biology 2012 (ECCB 2012) 2012.
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@inproceedings{Kalaghatgi2012Poster, TITLE = {A Pan-{E}uropean Phylodynamic Study of {HIV}-1 Transmission Networks}, AUTHOR = {Kalaghatgi, Prabhav and Lawyer, Glenn}, LANGUAGE = {eng}, YEAR = {2012}, DATE = {2012}, BOOKTITLE = {European Conference on Computational Biology 2012 (ECCB 2012)}, }
Endnote
%0 Generic %A Kalaghatgi, Prabhav %A Lawyer, Glenn %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T A Pan-European Phylodynamic Study of HIV-1 Transmission Networks : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0024-6F36-6 %D 2012 %Z name of event: European Conference on Computational Biology 2012 %Z date of event: 2012-09-08 - 2012-09-11 %Z place of event: %B European Conference on Computational Biology 2012
203. Kalinina OV, Oberwinkler H, Glass B, Krausslich H-G, Russell RB, Briggs JAG: Computational Identification of Novel Amino-Acid Interactions in HIV Gag via Correlated Evolution. PLoS One 2012, 7.
Abstract
Pairs of amino acid positions that evolve in a correlated manner are proposed to play important roles in protein structure or function. Methods to detect them might fare better with families for which sequences of thousands of closely related homologs are available than families with only a few distant relatives. We applied co-evolution analysis to thousands of sequences of HIV Gag, finding that the most significantly co-evolving positions are proximal in the quaternary structures of the viral capsid. A reduction in infectivity caused by mutating one member of a significant pair could be rescued by a compensatory mutation of the other.
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@article{Kalininar2012, TITLE = {Computational Identification of Novel Amino-Acid Interactions in {HIV} Gag via Correlated Evolution}, AUTHOR = {Kalinina, Olga V. and Oberwinkler, Heike and Glass, B{\"a}rbel and Krausslich, Hans-Georg and Russell, Robert B. and Briggs, John A. G.}, LANGUAGE = {eng}, ISSN = {1932-6203}, URL = {http://www.ncbi.nlm.nih.gov/pubmed/22879995}, DOI = {10.1371/journal.pone.0042468}, PUBLISHER = {Public Library of Science}, ADDRESS = {San Francisco, CA}, YEAR = {2012}, ABSTRACT = {Pairs of amino acid positions that evolve in a correlated manner are proposed to play important roles in protein structure or function. Methods to detect them might fare better with families for which sequences of thousands of closely related homologs are available than families with only a few distant relatives. We applied co-evolution analysis to thousands of sequences of HIV Gag, finding that the most significantly co-evolving positions are proximal in the quaternary structures of the viral capsid. A reduction in infectivity caused by mutating one member of a significant pair could be rescued by a compensatory mutation of the other.}, JOURNAL = {PLoS One}, VOLUME = {7}, NUMBER = {8}, PAGES = {e42468,1--e42468,5}, EID = {e42468}, }
Endnote
%0 Journal Article %A Kalinina, Olga V. %A Oberwinkler, Heike %A Glass, Bärbel %A Krausslich, Hans-Georg %A Russell, Robert B. %A Briggs, John A. G. %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations %T Computational Identification of Novel Amino-Acid Interactions in HIV Gag via Correlated Evolution : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-C8F4-0 %R 10.1371/journal.pone.0042468 %U http://www.ncbi.nlm.nih.gov/pubmed/22879995 %F OTHER: 231E99E1B252A1E3C1257B280046C6E3-Kalininar2012 %7 2012-08-03 %D 2012 %8 03.08.2012 %X Pairs of amino acid positions that evolve in a correlated manner are proposed to play important roles in protein structure or function. Methods to detect them might fare better with families for which sequences of thousands of closely related homologs are available than families with only a few distant relatives. We applied co-evolution analysis to thousands of sequences of HIV Gag, finding that the most significantly co-evolving positions are proximal in the quaternary structures of the viral capsid. A reduction in infectivity caused by mutating one member of a significant pair could be rescued by a compensatory mutation of the other. %K Amino Acid Sequence Amino Acids/*metabolism Computational Biology/*methods *Evolution, Molecular HIV/genetics/pathogenicity Models, Molecular Molecular Sequence Data gag Gene Products, Human Immunodeficiency Virus/*chemistry/*genetics %J PLoS One %V 7 %N 8 %& e42468,1 %P e42468,1 - e42468,5 %Z sequence number: e42468 %I Public Library of Science %C San Francisco, CA %@ false
204. König E: Automatic Detection of Loss of Heterozygosity in Cancer. Universität des Saarlandes; 2012.
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@mastersthesis{KoenigMaster2012, TITLE = {Automatic Detection of Loss of Heterozygosity in Cancer}, AUTHOR = {K{\"o}nig, Eva}, LANGUAGE = {eng}, LOCALID = {Local-ID: B5683407CE76C544C1257B270053FCFC-KoenigMaster2012}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2012}, DATE = {2012}, }
Endnote
%0 Thesis %A König, Eva %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Automatic Detection of Loss of Heterozygosity in Cancer : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-BA47-5 %F OTHER: Local-ID: B5683407CE76C544C1257B270053FCFC-KoenigMaster2012 %I Universität des Saarlandes %C Saarbrücken %D 2012 %V master %9 master
205. Koser S: Reconstructing Anecestral Methylation States in Phylogenetic Trees. Universität des Saarlandes; 2012.
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@mastersthesis{KoserMaster^2012, TITLE = {Reconstructing Anecestral Methylation States in Phylogenetic Trees}, AUTHOR = {Koser, Sandra}, LANGUAGE = {eng}, LOCALID = {Local-ID: 9EE6F63A0286B6B0C1257B270053D7D1-KoserMaster^2012}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2012}, DATE = {2012}, }
Endnote
%0 Thesis %A Koser, Sandra %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Reconstructing Anecestral Methylation States in Phylogenetic Trees : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-BA4A-0 %F OTHER: Local-ID: 9EE6F63A0286B6B0C1257B270053D7D1-KoserMaster^2012 %I Universität des Saarlandes %C Saarbrücken %D 2012 %V master %9 master
206. Lawyer G, Schülter E, Kaiser R, Reuter S, Oette M, Lengauer T: Endogenous or Exogenous Spreading of HIV-1 in Nordrhein-Westfalen, Germany, Investigated by Phylodynamic Analysis of the RESINA Study Cohort. Medical Microbiology and Immunology 2012, 201.
Abstract
HIV's genetic instability means that sequence similarity can illuminate the underlying transmission network. Previous application of such methods to samples from the United Kingdom has suggested that as many as 86% of UK infections arose outside of the country, a conclusion contrary to usual patterns of disease spread. We investigated transmission networks in the Resina cohort, a 2,747 member sample from Nordrhein-Westfalen, Germany, sequenced at therapy start. Transmission networks were determined by thresholding the pairwise genetic distance in the pol gene at 96.8% identity. At first blush the results concurred with the UK studies. Closer examination revealed four large and growing transmission networks that encompassed all major transmission groups. One of these formed a supercluster containing 71% of the sex with men (MSM) subjects when the network was thresholded at levels roughly equivalent to those used in the UK studies, though methodological differences suggest that this threshold may be too generous in the current data. Examination of the endo- versus exogenesis hypothesis by testing whether infections that were exogenous to Cologne or to Dusseldorf were endogenous to the greater region supported endogenous spread in MSM subjects and exogenous spread in the endemic transmission group. In intravenous drug using group subjects, it depended on viral strain, with subtype B sequences appearing to have origin exogenous to the Resina data, while non-B sequences (primarily subtype A) were almost completely endogenous to their local community. These results suggest that, at least in Germany, the question of endogenous versus exogenous linkages depends on subject group.
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@article{Lawyer2012, TITLE = {Endogenous or Exogenous Spreading of {HIV-1} in Nordrhein-Westfalen, Germany, Investigated by Phylodynamic Analysis of the {RESINA} Study Cohort}, AUTHOR = {Lawyer, Glenn and Sch{\"u}lter, Eugen and Kaiser, Rolf and Reuter, Stefan and Oette, Mark and Lengauer, Thomas and {RESINA Resarch Group}}, LANGUAGE = {eng}, ISSN = {0300-8584}, DOI = {10.1007/s00430-011-0228-8}, LOCALID = {Local-ID: 9AD835932963CE5FC1257AD20040FFB8-Lawyer2012}, PUBLISHER = {Springer}, ADDRESS = {New York, NY}, YEAR = {2012}, DATE = {2012}, ABSTRACT = {HIV's genetic instability means that sequence similarity can illuminate the underlying transmission network. Previous application of such methods to samples from the United Kingdom has suggested that as many as 86% of UK infections arose outside of the country, a conclusion contrary to usual patterns of disease spread. We investigated transmission networks in the Resina cohort, a 2,747 member sample from Nordrhein-Westfalen, Germany, sequenced at therapy start. Transmission networks were determined by thresholding the pairwise genetic distance in the pol gene at 96.8% identity. At first blush the results concurred with the UK studies. Closer examination revealed four large and growing transmission networks that encompassed all major transmission groups. One of these formed a supercluster containing 71% of the sex with men (MSM) subjects when the network was thresholded at levels roughly equivalent to those used in the UK studies, though methodological differences suggest that this threshold may be too generous in the current data. Examination of the endo- versus exogenesis hypothesis by testing whether infections that were exogenous to Cologne or to Dusseldorf were endogenous to the greater region supported endogenous spread in MSM subjects and exogenous spread in the endemic transmission group. In intravenous drug using group subjects, it depended on viral strain, with subtype B sequences appearing to have origin exogenous to the Resina data, while non-B sequences (primarily subtype A) were almost completely endogenous to their local community. These results suggest that, at least in Germany, the question of endogenous versus exogenous linkages depends on subject group.}, JOURNAL = {Medical Microbiology and Immunology}, VOLUME = {201}, NUMBER = {3}, PAGES = {259--269}, }
Endnote
%0 Journal Article %A Lawyer, Glenn %A Schülter, Eugen %A Kaiser, Rolf %A Reuter, Stefan %A Oette, Mark %A Lengauer, Thomas %A RESINA Resarch Group, %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Endogenous or Exogenous Spreading of HIV-1 in Nordrhein-Westfalen, Germany, Investigated by Phylodynamic Analysis of the RESINA Study Cohort : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-C8F1-5 %R 10.1007/s00430-011-0228-8 %F OTHER: Local-ID: 9AD835932963CE5FC1257AD20040FFB8-Lawyer2012 %7 2012-01-20 %D 2012 %X HIV's genetic instability means that sequence similarity can illuminate the underlying transmission network. Previous application of such methods to samples from the United Kingdom has suggested that as many as 86% of UK infections arose outside of the country, a conclusion contrary to usual patterns of disease spread. We investigated transmission networks in the Resina cohort, a 2,747 member sample from Nordrhein-Westfalen, Germany, sequenced at therapy start. Transmission networks were determined by thresholding the pairwise genetic distance in the pol gene at 96.8% identity. At first blush the results concurred with the UK studies. Closer examination revealed four large and growing transmission networks that encompassed all major transmission groups. One of these formed a supercluster containing 71% of the sex with men (MSM) subjects when the network was thresholded at levels roughly equivalent to those used in the UK studies, though methodological differences suggest that this threshold may be too generous in the current data. Examination of the endo- versus exogenesis hypothesis by testing whether infections that were exogenous to Cologne or to Dusseldorf were endogenous to the greater region supported endogenous spread in MSM subjects and exogenous spread in the endemic transmission group. In intravenous drug using group subjects, it depended on viral strain, with subtype B sequences appearing to have origin exogenous to the Resina data, while non-B sequences (primarily subtype A) were almost completely endogenous to their local community. These results suggest that, at least in Germany, the question of endogenous versus exogenous linkages depends on subject group. %K Cohort Studies Endemic Diseases Female Germany/epidemiology HIV Infections/*epidemiology/*transmission/virology HIV-1/*genetics Heterosexuality Homosexuality, Male Humans Male *Molecular Epidemiology Prospective Studies Substance Abuse, Intravenous/complications %J Medical Microbiology and Immunology %O Med. Microbiol. Immunol. %V 201 %N 3 %& 259 %P 259 - 269 %I Springer %C New York, NY %@ false
207. Lengauer T: Bioinformatical Assistance of Selecting Anti-HIV Therapies: Where Do We Stand? Intervirology 2012, 55.
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@article{Lengauer2012z, TITLE = {Bioinformatical Assistance of Selecting Anti-{HIV} Therapies: {Where} Do We Stand?}, AUTHOR = {Lengauer, Thomas}, LANGUAGE = {eng}, DOI = {10.1159/000332000}, LOCALID = {Local-ID: 5FD44ECAFCBC86ABC1257B1200419E45-Lengauer2012z}, PUBLISHER = {Karger}, ADDRESS = {Basel}, YEAR = {2012}, DATE = {2012}, JOURNAL = {Intervirology}, VOLUME = {55}, NUMBER = {2}, PAGES = {108--112}, }
Endnote
%0 Journal Article %A Lengauer, Thomas %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Bioinformatical Assistance of Selecting Anti-HIV Therapies: Where Do We Stand? : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-BAF4-0 %R 10.1159/000332000 %F OTHER: Local-ID: 5FD44ECAFCBC86ABC1257B1200419E45-Lengauer2012z %7 2012-01-24 %D 2012 %J Intervirology %V 55 %N 2 %& 108 %P 108 - 112 %I Karger %C Basel
208. Lengauer T, Albrecht M, Domingues FS: Computational Biology. In Encyclopedia of Molecular Cell Biology and Molecular Medicine. Weinheim, Germany: Wiley-VCH; 2012.
Abstract
During recent years, biological research has become increasingly based on large-scale experimentation such that data may be collected on an organismic scale. These data are voluminous, they are often very noisy, and their interpretation � and the configuration of the experiments involved � necessitates complex computer analysis. The respective computer methods are themselves an object of intensive research in a scientific discipline known as "computational biology" or "bioinformatics." Computational biology has a wide variety of facets that range from experiment configuration and low-level data analysis to computer-generated hypotheses.
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@incollection{Albrecht2012g, TITLE = {Computational Biology}, AUTHOR = {Lengauer, Thomas and Albrecht, Mario and Domingues, Francisco S.}, LANGUAGE = {eng}, ISBN = {978-3-527-60090-8}, DOI = {10.1002/3527600906.mcb.200400023.pub2; 10.1002/3527600906}, LOCALID = {Local-ID: C6545BDC6EE10AB7C1257AD9003E8B44-Albrecht2012g}, PUBLISHER = {Wiley-VCH}, ADDRESS = {Weinheim, Germany}, YEAR = {2012}, ABSTRACT = {During recent years, biological research has become increasingly based on large-scale experimentation such that data may be collected on an organismic scale. These data are voluminous, they are often very noisy, and their interpretation {\diamond} and the configuration of the experiments involved {\diamond} necessitates complex computer analysis. The respective computer methods are themselves an object of intensive research in a scientific discipline known as "computational biology" or "bioinformatics." Computational biology has a wide variety of facets that range from experiment configuration and low-level data analysis to computer-generated hypotheses.}, BOOKTITLE = {Encyclopedia of Molecular Cell Biology and Molecular Medicine}, EDITOR = {Meyers, Robert A.}, PAGES = {1--71}, }
Endnote
%0 Book Section %A Lengauer, Thomas %A Albrecht, Mario %A Domingues, Francisco S. %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Computational Biology : %G eng %U http://hdl.handle.net/11858/00-001M-0000-0014-C521-F %R 10.1002/3527600906.mcb.200400023.pub2 %F OTHER: Local-ID: C6545BDC6EE10AB7C1257AD9003E8B44-Albrecht2012g %D 2012 %8 15.05.2012 %X During recent years, biological research has become increasingly based on large-scale experimentation such that data may be collected on an organismic scale. These data are voluminous, they are often very noisy, and their interpretation � and the configuration of the experiments involved � necessitates complex computer analysis. The respective computer methods are themselves an object of intensive research in a scientific discipline known as "computational biology" or "bioinformatics." Computational biology has a wide variety of facets that range from experiment configuration and low-level data analysis to computer-generated hypotheses. %B Encyclopedia of Molecular Cell Biology and Molecular Medicine %E Meyers, Robert A. %P 1 - 71 %I Wiley-VCH %C Weinheim, Germany %@ 978-3-527-60090-8
209. Mekhubad S, Bock C, de Boer AS, Kiskinis E, Meissner A, Eggan K: Erosion of Dosage Compensation Impacts Human iPSC Disease Modeling. Cell Stem Cell 2012, 10.