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1. Allison TF, Andrews PW, Avior Y, Barbaric I, Benvenisty N, Bock C, Brehm J, Bruestle O, Damjanov I, Elefanty A, Felkner D, Gokhale PJ, Halbritter F, Healy LE, Hu TX, Knowles BB, Loring JF, Ludwig TE, Mayberry R, Micallef S, Mohamed JS, Mueller F-J, Mummery CL, Nakatsuji N, Ng ES, Oh SKW, O’Shea O, Pera MF, Reubinoff B, Robson P, et al.: Assessment of Established Techniques to Determine Developmental and Malignant Potential of Human Pluripotent Stem Cells. Nature Communications 2018.
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@article{Allison2018, TITLE = {Assessment of Established Techniques to Determine Developmental and Malignant Potential of Human Pluripotent Stem Cells}, AUTHOR = {Allison, Thomas F. and Andrews, Peter W. and Avior, Yishai and Barbaric, Ivana and Benvenisty, Nissim and Bock, Christoph and Brehm, Jennifer and Bruestle, Oliver and Damjanov, Ivan and Elefanty, Andrew and Felkner, Daniel and Gokhale, Paul J. and Halbritter, Florian and Healy, Lyn E. and Hu, Tim X. and Knowles, Barbara B. and Loring, Jeanne F. and Ludwig, Tenneille E. and Mayberry, Robyn and Micallef, Suzanne and Mohamed, Jameelah S. and Mueller, Franz-Josef and Mummery, Christine L. and Nakatsuji, Norio and Ng, Elizabeth S. and Oh, Steve K. W. and O'Shea, Orla and Pera, Martin F. and Reubinoff, Benjamin and Robson, Paul and Rossant, Janet and Schuldt, Bernhard M. and Solter, Davor and Sourris, Koula and Stacey, Glyn and Stanley, Edouard G. and Suemori, Hirofumi and Takahashi, Kazutoshi and Yamanaka, Shinya}, LANGUAGE = {eng}, ISSN = {2041-1723}, DOI = {10.1038/s41467-018-04011-3}, PUBLISHER = {Nature Publishing Group}, ADDRESS = {London}, YEAR = {2018}, JOURNAL = {Nature Communications}, EID = {1925}, }
Endnote
%0 Journal Article %A Allison, Thomas F. %A Andrews, Peter W. %A Avior, Yishai %A Barbaric, Ivana %A Benvenisty, Nissim %A Bock, Christoph %A Brehm, Jennifer %A Bruestle, Oliver %A Damjanov, Ivan %A Elefanty, Andrew %A Felkner, Daniel %A Gokhale, Paul J. %A Halbritter, Florian %A Healy, Lyn E. %A Hu, Tim X. %A Knowles, Barbara B. %A Loring, Jeanne F. %A Ludwig, Tenneille E. %A Mayberry, Robyn %A Micallef, Suzanne %A Mohamed, Jameelah S. %A Mueller, Franz-Josef %A Mummery, Christine L. %A Nakatsuji, Norio %A Ng, Elizabeth S. %A Oh, Steve K. W. %A O'Shea, Orla %A Pera, Martin F. %A Reubinoff, Benjamin %A Robson, Paul %A Rossant, Janet %A Schuldt, Bernhard M. %A Solter, Davor %A Sourris, Koula %A Stacey, Glyn %A Stanley, Edouard G. %A Suemori, Hirofumi %A Takahashi, Kazutoshi %A Yamanaka, Shinya %+ 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 %T Assessment of Established Techniques to Determine Developmental and Malignant Potential of Human Pluripotent Stem Cells : %G eng %U http://hdl.handle.net/21.11116/0000-0001-66DB-6 %R 10.1038/s41467-018-04011-3 %7 2018 %D 2018 %J Nature Communications %O Nat. Commun. %Z sequence number: 1925 %I Nature Publishing Group %C London %@ false
2. Apweiler R, Beissbarth T, Berthold MR, Bluethgen N, Burmeister Y, Dammann O, Deutsch A, Feuerhake F, Franke A, Hasenauer J, Hoffmann S, Hoefer T, Jansen PLM, Kaderali L, Klingmueller U, Koch I, Kohlbacher O, Kuepfer L, Lammert F, Maier D, Pfeifer N, Radde N, Rehm M, Roeder I, Saez-Rodriguez J, Sax U, Schmeck B, Schuppert A, Seilheimer B, Theis FJ, et al.: Whither systems medicine?Experimental & Molecular Medicine 2018, 50.
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@article{Apweiler2018, TITLE = {Whither systems medicine?}, AUTHOR = {Apweiler, Rolf and Beissbarth, Tim and Berthold, Michael R. and Bluethgen, Nils and Burmeister, Yvonne and Dammann, Olaf and Deutsch, Andreas and Feuerhake, Friedrich and Franke, Andre and Hasenauer, Jan and Hoffmann, Steve and Hoefer, Thomas and Jansen, Peter L. M. and Kaderali, Lars and Klingmueller, Ursula and Koch, Ina and Kohlbacher, Oliver and Kuepfer, Lars and Lammert, Frank and Maier, Dieter and Pfeifer, Nico and Radde, Nicole and Rehm, Markus and Roeder, Ingo and Saez-Rodriguez, Julio and Sax, Ulrich and Schmeck, Bernd and Schuppert, Andreas and Seilheimer, Bernd and Theis, Fabian J. and Vera, Julio and Wolkenhauer, Olaf}, LANGUAGE = {eng}, ISSN = {2092-6413}, DOI = {10.1038/emm.2017.290}, PUBLISHER = {Korean Society of Medical Biochemistry and Molecular Biology}, ADDRESS = {Seoul}, YEAR = {2018}, DATE = {2018}, JOURNAL = {Experimental \& Molecular Medicine}, VOLUME = {50}, EID = {e453}, }
Endnote
%0 Journal Article %A Apweiler, Rolf %A Beissbarth, Tim %A Berthold, Michael R. %A Bluethgen, Nils %A Burmeister, Yvonne %A Dammann, Olaf %A Deutsch, Andreas %A Feuerhake, Friedrich %A Franke, Andre %A Hasenauer, Jan %A Hoffmann, Steve %A Hoefer, Thomas %A Jansen, Peter L. M. %A Kaderali, Lars %A Klingmueller, Ursula %A Koch, Ina %A Kohlbacher, Oliver %A Kuepfer, Lars %A Lammert, Frank %A Maier, Dieter %A Pfeifer, Nico %A Radde, Nicole %A Rehm, Markus %A Roeder, Ingo %A Saez-Rodriguez, Julio %A Sax, Ulrich %A Schmeck, Bernd %A Schuppert, Andreas %A Seilheimer, Bernd %A Theis, Fabian J. %A Vera, Julio %A Wolkenhauer, Olaf %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations 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 %T Whither systems medicine? : %G eng %U http://hdl.handle.net/21.11116/0000-0001-2D95-5 %R 10.1038/emm.2017.290 %7 2018 %D 2018 %J Experimental & Molecular Medicine %O EMM %V 50 %Z sequence number: e453 %I Korean Society of Medical Biochemistry and Molecular Biology %C Seoul %@ false
3. Barakat TS, Halbritter F, Zhang M, Rendeiro AF, Perenthaler E, Bock C, Chambers I: Functional Dissection of the Enhancer Repertoire in Human Embryonic Stem Cells. Cell Stem Cell 2018, 23.
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@article{Bakarat2018, TITLE = {Functional Dissection of the Enhancer Repertoire in Human Embryonic Stem Cells}, AUTHOR = {Barakat, Tahsin Stefan and Halbritter, Florian and Zhang, Man and Rendeiro, Andre F. and Perenthaler, Elena and Bock, Christoph and Chambers, Ian}, LANGUAGE = {eng}, ISSN = {1934-5909; 1875-9777}, DOI = {10.1016/j.stem.2018.06.014}, PUBLISHER = {Elsevier}, ADDRESS = {Amsterdam}, YEAR = {2018}, DATE = {2018}, JOURNAL = {Cell Stem Cell}, VOLUME = {23}, NUMBER = {2}, PAGES = {276--288}, EID = {e8}, }
Endnote
%0 Journal Article %A Barakat, Tahsin Stefan %A Halbritter, Florian %A Zhang, Man %A Rendeiro, Andre F. %A Perenthaler, Elena %A Bock, Christoph %A Chambers, Ian %+ External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T Functional Dissection of the Enhancer Repertoire in Human Embryonic Stem Cells : %G eng %U http://hdl.handle.net/21.11116/0000-0001-EE1A-7 %R 10.1016/j.stem.2018.06.014 %7 2018 %D 2018 %J Cell Stem Cell %V 23 %N 2 %& 276 %P 276 - 288 %Z sequence number: e8 %I Elsevier %C Amsterdam %@ false
4. Bastys T, Gapsys V, Doncheva NT, Kaiser R, de Groot BL, Kalinina OV: Consistent Prediction of Mutation Effect on Drug Binding in HIV-1 Protease Using Alchemical Calculations. Journal of Chemical Theory and Computation 2018, 14.
Abstract
Despite of a large number of antiretroviral drugs targeting HIV-1 protease for inhibition, mutations in this protein during the course of patient treatment can render them inefficient. This emerging resistance inspired numerous computational studies of the HIV-1 protease aimed at predicting the effect of mutations on drug binding in terms of free binding energy $\Delta G$, as well as in mechanistic terms. In this study, we analyse ten different protease-inhibitor complexes carrying major resistance-associated mutations (RAMs) G48V, I50V, and L90M using molecular dynamics simulations. We demonstrate that alchemical free energy calculations can consistently predict the effect of mutations on drug binding. By explicitly probing different protonation states of the catalytic aspartic dyad, we reveal the importance of the correct choice of protonation state for the accuracy of the result. We also provide insight into how different mutations affect drug binding in their specific ways, with the unifying theme of how all of them affect the crucial for drug binding regions of the protease.
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@article{Bastys2018, TITLE = {Consistent Prediction of Mutation Effect on Drug Binding in {HIV}-1 Protease Using Alchemical Calculations}, AUTHOR = {Bastys, Tomas and Gapsys, Vytautas and Doncheva, Nadezhda Tsankova and Kaiser, Rolf and de Groot, Bert L. and Kalinina, Olga V.}, LANGUAGE = {eng}, DOI = {10.1021/acs.jctc.7b01109}, PUBLISHER = {American Chemical Society}, ADDRESS = {Washington, D.C.}, YEAR = {2018}, DATE = {2018}, ABSTRACT = {Despite of a large number of antiretroviral drugs targeting HIV-1 protease for inhibition, mutations in this protein during the course of patient treatment can render them inefficient. This emerging resistance inspired numerous computational studies of the HIV-1 protease aimed at predicting the effect of mutations on drug binding in terms of free binding energy $\Delta G$, as well as in mechanistic terms. In this study, we analyse ten different protease-inhibitor complexes carrying major resistance-associated mutations (RAMs) G48V, I50V, and L90M using molecular dynamics simulations. We demonstrate that alchemical free energy calculations can consistently predict the effect of mutations on drug binding. By explicitly probing different protonation states of the catalytic aspartic dyad, we reveal the importance of the correct choice of protonation state for the accuracy of the result. We also provide insight into how different mutations affect drug binding in their specific ways, with the unifying theme of how all of them affect the crucial for drug binding regions of the protease.}, JOURNAL = {Journal of Chemical Theory and Computation}, VOLUME = {14}, NUMBER = {7}, PAGES = {3397--3408}, }
Endnote
%0 Journal Article %A Bastys, Tomas %A Gapsys, Vytautas %A Doncheva, Nadezhda Tsankova %A Kaiser, Rolf %A de Groot, Bert L. %A Kalinina, Olga V. %+ 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 Consistent Prediction of Mutation Effect on Drug Binding in HIV-1 Protease Using Alchemical Calculations : %G eng %U http://hdl.handle.net/21.11116/0000-0001-E5BA-B %R 10.1021/acs.jctc.7b01109 %7 2018-05-30 %D 2018 %* Review method: peer-reviewed %X Despite of a large number of antiretroviral drugs targeting HIV-1 protease for inhibition, mutations in this protein during the course of patient treatment can render them inefficient. This emerging resistance inspired numerous computational studies of the HIV-1 protease aimed at predicting the effect of mutations on drug binding in terms of free binding energy $\Delta G$, as well as in mechanistic terms. In this study, we analyse ten different protease-inhibitor complexes carrying major resistance-associated mutations (RAMs) G48V, I50V, and L90M using molecular dynamics simulations. We demonstrate that alchemical free energy calculations can consistently predict the effect of mutations on drug binding. By explicitly probing different protonation states of the catalytic aspartic dyad, we reveal the importance of the correct choice of protonation state for the accuracy of the result. We also provide insight into how different mutations affect drug binding in their specific ways, with the unifying theme of how all of them affect the crucial for drug binding regions of the protease. %J Journal of Chemical Theory and Computation %O J. Chem. Theory Comput. %V 14 %N 7 %& 3397 %P 3397 - 3408 %I American Chemical Society %C Washington, D.C.
5. Baumgartner C, Toifl S, Farlik M, Halbritter F, Scheicher R, Fischer I, Sexl V, Bock C, Baccarini M: An ERK-Dependent Feedback Mechanism Prevents Hematopoietic Stem Cell Exhaustion. Cell Stem Cell 2018, 22.
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@article{Baumgartner2018, TITLE = {An {ERK}-Dependent Feedback Mechanism Prevents Hematopoietic Stem Cell Exhaustion}, AUTHOR = {Baumgartner, Christian and Toifl, Stefanie and Farlik, Matthias and Halbritter, Florian and Scheicher, Ruth and Fischer, Irmgard and Sexl, Veronika and Bock, Christoph and Baccarini, Manuela}, LANGUAGE = {eng}, ISSN = {1934-5909}, DOI = {10.1016/j.stem.2018.05.003}, PUBLISHER = {Cell Press}, ADDRESS = {Cambridge, Mass.}, YEAR = {2018}, DATE = {2018}, JOURNAL = {Cell Stem Cell}, VOLUME = {22}, NUMBER = {6}, PAGES = {879--892}, EID = {e6}, }
Endnote
%0 Journal Article %A Baumgartner, Christian %A Toifl, Stefanie %A Farlik, Matthias %A Halbritter, Florian %A Scheicher, Ruth %A Fischer, Irmgard %A Sexl, Veronika %A Bock, Christoph %A Baccarini, Manuela %+ 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 An ERK-Dependent Feedback Mechanism Prevents Hematopoietic Stem Cell Exhaustion : %G eng %U http://hdl.handle.net/21.11116/0000-0001-88D5-5 %R 10.1016/j.stem.2018.05.003 %7 2018 %D 2018 %J Cell Stem Cell %V 22 %N 6 %& 879 %P 879 - 892 %Z sequence number: e6 %I Cell Press %C Cambridge, Mass. %@ false
6. Chakraborty S, Canzar S, Marschall T, Schulz MH: Chromatyping: Reconstructing Nucleosome Profiles from NOMe Sequencing Data. In Research in Computational Molecular Biology (RECOMB 2018). Springer; 2018. [Lecture Notes in Bioinformatics, vol. 10812]
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@inproceedings{Chakraborty_RECOMB2018, TITLE = {Chromatyping: {R}econstructing Nucleosome Profiles from {NOMe} Sequencing Data}, AUTHOR = {Chakraborty, Shounak and Canzar, Stefan and Marschall, Tobias and Schulz, Marcel H.}, LANGUAGE = {eng}, ISBN = {978-3-319-89928-2}, DOI = {10.1007/978-3-319-89929-9_2}, PUBLISHER = {Springer}, YEAR = {2018}, DATE = {2018}, BOOKTITLE = {Research in Computational Molecular Biology (RECOMB 2018)}, EDITOR = {Raphael, Benjamin H.}, PAGES = {21--36}, SERIES = {Lecture Notes in Bioinformatics}, VOLUME = {10812}, ADDRESS = {Paris, France}, }
Endnote
%0 Conference Proceedings %A Chakraborty, Shounak %A Canzar, Stefan %A Marschall, Tobias %A Schulz, Marcel H. %+ 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 Chromatyping: Reconstructing Nucleosome Profiles from NOMe Sequencing Data : %G eng %U http://hdl.handle.net/21.11116/0000-0001-404B-3 %R 10.1007/978-3-319-89929-9_2 %D 2018 %B 22nd International Conference on Research in Computational Molecular Biology %Z date of event: 2018-04-21 - 2018-04-24 %C Paris, France %B Research in Computational Molecular Biology %E Raphael, Benjamin H. %P 21 - 36 %I Springer %@ 978-3-319-89928-2 %B Lecture Notes in Bioinformatics %N 10812
7. Döring M, Büch J, Friedrich G, Pironti A, Kalaghatgi P, Knops E, Heger E, Obermeier M, Däumer M, Thielen A, Kaiser R, Lengauer T, Pfeifer N: Geno2pheno[ngs-freq]: a Genotypic Interpretation System for Identifying Viral Drug Resistance using Next-Generation Sequencing Data. Nucleic Acids Research 2018, 46(Web Server issue).
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@article{Doering2018, TITLE = {Geno2pheno[ngs-freq]: a Genotypic Interpretation System for Identifying Viral Drug Resistance using Next-Generation Sequencing Data}, AUTHOR = {D{\"o}ring, Matthias and B{\"u}ch, Joachim and Friedrich, Georg and Pironti, Alejandro and Kalaghatgi, Prabhav and Knops, Elena and Heger, Eva and Obermeier, Martin and D{\"a}umer, Martin and Thielen, Alexander and Kaiser, Rolf and Lengauer, Thomas and Pfeifer, Nico}, LANGUAGE = {eng}, ISSN = {0305-1048}, DOI = {10.1093/nar/gky349}, PUBLISHER = {Oxford University Press}, ADDRESS = {Oxford}, YEAR = {2018}, DATE = {2018}, JOURNAL = {Nucleic Acids Research}, VOLUME = {46}, NUMBER = {Web Server issue}, PAGES = {W271--W277}, EID = {gky349}, }
Endnote
%0 Journal Article %A Döring, Matthias %A Büch, Joachim %A Friedrich, Georg %A Pironti, Alejandro %A Kalaghatgi, Prabhav %A Knops, Elena %A Heger, Eva %A Obermeier, Martin %A Däumer, Martin %A Thielen, Alexander %A Kaiser, Rolf %A Lengauer, Thomas %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 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 Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Geno2pheno[ngs-freq]: a Genotypic Interpretation System for Identifying Viral Drug Resistance using Next-Generation Sequencing Data : %G eng %U http://hdl.handle.net/21.11116/0000-0001-3F53-C %R 10.1093/nar/gky349 %2 PMC6031006 %7 2018 %D 2018 %J Nucleic Acids Research %O Nucleic Acids Res %V 46 %N Web Server issue %& W271 %P W271 - W277 %Z sequence number: gky349 %I Oxford University Press %C Oxford %@ false
8. Fun A, Leitner T, Vandekerckhove L, Däumer M, Thielen A, Buchholz B, Hoepelman AIM, Gisolf EH, Schipper PJ, Wensing AMJ, Nijhuis M: Impact of the HIV-1 Genetic Background and HIV-1 Population Size on the Evolution of Raltegravir Resistance. Retrovirology 2018, 15.
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@article{Fun2018, TITLE = {Impact of the {HIV}-1 Genetic Background and {HIV}-1 Population Size on the Evolution of Raltegravir Resistance}, AUTHOR = {Fun, Axel and Leitner, Thomas and Vandekerckhove, Linos and D{\"a}umer, Martin and Thielen, Alexander and Buchholz, Bernd and Hoepelman, Andy I. M. and Gisolf, Elizabeth H. and Schipper, Pauline J. and Wensing, Annemarie M. J. and Nijhuis, Monique}, LANGUAGE = {eng}, ISSN = {1742-4690}, DOI = {10.1186/s12977-017-0384-z}, PUBLISHER = {BioMed Central}, ADDRESS = {London}, YEAR = {2018}, DATE = {2018}, JOURNAL = {Retrovirology}, VOLUME = {15}, EID = {1}, }
Endnote
%0 Journal Article %A Fun, Axel %A Leitner, Thomas %A Vandekerckhove, Linos %A Däumer, Martin %A Thielen, Alexander %A Buchholz, Bernd %A Hoepelman, Andy I. M. %A Gisolf, Elizabeth H. %A Schipper, Pauline J. %A Wensing, Annemarie M. J. %A Nijhuis, Monique %+ 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 Impact of the HIV-1 Genetic Background and HIV-1 Population Size on the Evolution of Raltegravir Resistance : %G eng %U http://hdl.handle.net/21.11116/0000-0000-376A-C %R 10.1186/s12977-017-0384-z %7 2018 %D 2018 %J Retrovirology %V 15 %Z sequence number: 1 %I BioMed Central %C London %@ false
9. Garg S, Rautiainen M, Novak AM, Garrison E, Durbin R, Marschall T: A Graph-based Approach to Diploid Genome Assembly. Bioinformatics (Proc ISMB 2018) 2018, 34.
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@article{Garg_Bioinformatics2018, TITLE = {A Graph-based Approach to Diploid Genome Assembly}, AUTHOR = {Garg, Shilpa and Rautiainen, Mikko and Novak, Adam M. and Garrison, Erik and Durbin, Richard and Marschall, Tobias}, LANGUAGE = {eng}, ISSN = {1367-4803}, DOI = {10.1093/bioinformatics/bty279}, PUBLISHER = {Oxford University Press}, ADDRESS = {Oxford}, YEAR = {2018}, DATE = {2018}, JOURNAL = {Bioinformatics (Proc. ISMB)}, VOLUME = {34}, PAGES = {i105--i114}, BOOKTITLE = {ISMB 2018 Proceedings}, }
Endnote
%0 Journal Article %A Garg, Shilpa %A Rautiainen, Mikko %A Novak, Adam M. %A Garrison, Erik %A Durbin, Richard %A Marschall, Tobias %+ 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 A Graph-based Approach to Diploid Genome Assembly : %G eng %U http://hdl.handle.net/21.11116/0000-0001-E5A6-1 %R 10.1093/bioinformatics/bty279 %7 2018 %D 2018 %J Bioinformatics %V 34 %& i105 %P i105 - i114 %I Oxford University Press %C Oxford %@ false %B ISMB 2018 Proceedings %O ISMB 2018 July 6 to July 10, 2018, Chicago, IL, United States
10. Garg S: Computational Haplotyping: theory and practice. Universität des Saarlandes; 2018.
Abstract
Genomics has paved a new way to comprehend life and its evolution, and also to investigate causes of diseases and their treatment. One of the important problems in genomic analyses is haplotype assembly. Constructing complete and accurate haplotypes plays an essential role in understanding population genetics and how species evolve. In this thesis, we focus on computational approaches to haplotype assembly from third generation sequencing technologies. This involves huge amounts of sequencing data, and such data contain errors due to the single molecule sequencing protocols employed. Taking advantage of combinatorial formulations helps to correct for these errors to solve the haplotyping problem. Various computational techniques such as dynamic programming, parameterized algorithms, and graph algorithms are used to solve this problem. This thesis presents several contributions concerning the area of haplotyping. First, a novel algorithm based on dynamic programming is proposed to provide approximation guarantees for phasing a single individual. Second, an integrative approach is introduced to combining multiple sequencing datasets to generating complete and accurate haplotypes. The effectiveness of this integrative approach is demonstrated on a real human genome. Third, we provide a novel efficient approach to phasing pedigrees and demonstrate its advantages in comparison to phasing a single individual. Fourth, we present a generalized graph-based framework for performing haplotype-aware de novo assembly. Specifically, this generalized framework consists of a hybrid pipeline for generating accurate and complete haplotypes from data stemming from multiple sequencing technologies, one that provides accurate reads and other that provides long reads.
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@phdthesis{gargphd2017, TITLE = {Computational Haplotyping: theory and practice}, AUTHOR = {Garg, Shilpa}, LANGUAGE = {eng}, DOI = {10.22028/D291-27252}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2018}, DATE = {2018}, ABSTRACT = {Genomics has paved a new way to comprehend life and its evolution, and also to investigate causes of diseases and their treatment. One of the important problems in genomic analyses is haplotype assembly. Constructing complete and accurate haplotypes plays an essential role in understanding population genetics and how species evolve. In this thesis, we focus on computational approaches to haplotype assembly from third generation sequencing technologies. This involves huge amounts of sequencing data, and such data contain errors due to the single molecule sequencing protocols employed. Taking advantage of combinatorial formulations helps to correct for these errors to solve the haplotyping problem. Various computational techniques such as dynamic programming, parameterized algorithms, and graph algorithms are used to solve this problem. This thesis presents several contributions concerning the area of haplotyping. First, a novel algorithm based on dynamic programming is proposed to provide approximation guarantees for phasing a single individual. Second, an integrative approach is introduced to combining multiple sequencing datasets to generating complete and accurate haplotypes. The effectiveness of this integrative approach is demonstrated on a real human genome. Third, we provide a novel efficient approach to phasing pedigrees and demonstrate its advantages in comparison to phasing a single individual. Fourth, we present a generalized graph-based framework for performing haplotype-aware de novo assembly. Specifically, this generalized framework consists of a hybrid pipeline for generating accurate and complete haplotypes from data stemming from multiple sequencing technologies, one that provides accurate reads and other that provides long reads.}, }
Endnote
%0 Thesis %A Garg, Shilpa %Y Marschall, Tobias %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 Haplotyping: theory and practice : %G eng %U http://hdl.handle.net/21.11116/0000-0001-9D80-D %R 10.22028/D291-27252 %I Universität des Saarlandes %C Saarbrücken %D 2018 %P 119 p. %V phd %9 phd %X Genomics has paved a new way to comprehend life and its evolution, and also to investigate causes of diseases and their treatment. One of the important problems in genomic analyses is haplotype assembly. Constructing complete and accurate haplotypes plays an essential role in understanding population genetics and how species evolve. In this thesis, we focus on computational approaches to haplotype assembly from third generation sequencing technologies. This involves huge amounts of sequencing data, and such data contain errors due to the single molecule sequencing protocols employed. Taking advantage of combinatorial formulations helps to correct for these errors to solve the haplotyping problem. Various computational techniques such as dynamic programming, parameterized algorithms, and graph algorithms are used to solve this problem. This thesis presents several contributions concerning the area of haplotyping. First, a novel algorithm based on dynamic programming is proposed to provide approximation guarantees for phasing a single individual. Second, an integrative approach is introduced to combining multiple sequencing datasets to generating complete and accurate haplotypes. The effectiveness of this integrative approach is demonstrated on a real human genome. Third, we provide a novel efficient approach to phasing pedigrees and demonstrate its advantages in comparison to phasing a single individual. Fourth, we present a generalized graph-based framework for performing haplotype-aware de novo assembly. Specifically, this generalized framework consists of a hybrid pipeline for generating accurate and complete haplotypes from data stemming from multiple sequencing technologies, one that provides accurate reads and other that provides long reads. %U https://publikationen.sulb.uni-saarland.de/handle/20.500.11880/27102
11. Ghareghani M, Porubsky D, Sanders AD, Meiers S, Eichler EE, Korbel JO, Marschall T: Strand-seq Enables Reliable Separation of Long Reads by Chromosome via Expectation Maximization. Bioinformatics (Proc ISMB 2018) 2018, 34.
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@article{Ghareghani_ISMB2018, TITLE = {Strand-seq Enables Reliable Separation of Long Reads by Chromosome via Expectation Maximization}, AUTHOR = {Ghareghani, Maryam and Porubsky, David and Sanders, Ashley D. and Meiers, Sascha and Eichler, Evan E. and Korbel, Jan O. and Marschall, Tobias}, LANGUAGE = {eng}, ISSN = {1367-4803}, DOI = {10.1093/bioinformatics/bty290}, PUBLISHER = {Oxford University Press}, ADDRESS = {Oxford}, YEAR = {2018}, DATE = {2018}, JOURNAL = {Bioinformatics (Proc. ISMB)}, VOLUME = {34}, NUMBER = {13}, PAGES = {i115--I123}, BOOKTITLE = {ISMB 2018 Proceedings}, }
Endnote
%0 Journal Article %A Ghareghani, Maryam %A Porubsky, David %A Sanders, Ashley D. %A Meiers, Sascha %A Eichler, Evan E. %A Korbel, Jan O. %A Marschall, Tobias %+ 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 Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Strand-seq Enables Reliable Separation of Long Reads by Chromosome via Expectation Maximization : %G eng %U http://hdl.handle.net/21.11116/0000-0001-E5AA-D %R 10.1093/bioinformatics/bty290 %7 2018 %D 2018 %J Bioinformatics %V 34 %N 13 %& i115 %P i115 - I123 %I Oxford University Press %C Oxford %@ false %B ISMB 2018 Proceedings %O July 6 to July 10, 2018, Chicago, IL, United States ISMB 2018
12. Goeschl L, Preglej T, Hamminger P, Bonelli M, Andersen L, Boucheron N, Guelich AF, Mueller L, Saferding V, Mufazalov IA, Hirahara K, Seiser C, Matthias P, Penz T, Schuster M, Bock C, Waisman A, Steiner G, Ellmeier W: A T Cell-specific Deletion of HDAC1 Protects Against Experimental Autoimmune Encephalomyelitis. Journal of Autoimmunity 2018, 86.
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@article{Goeschl2018, TITLE = {A {T} Cell-specific Deletion of {HDAC}1 Protects Against Experimental Autoimmune Encephalomyelitis}, AUTHOR = {Goeschl, Lisa and Preglej, Teresa and Hamminger, Patricia and Bonelli, Michael and Andersen, Liisa and Boucheron, Nicole and Guelich, Alexandra F. and Mueller, Lena and Saferding, Victoria and Mufazalov, Ilgiz A. and Hirahara, Kiyoshi and Seiser, Christian and Matthias, Patrick and Penz, Thomas and Schuster, Michael and Bock, Christoph and Waisman, Ari and Steiner, Guenter and Ellmeier, Wilfried}, LANGUAGE = {eng}, ISSN = {0896-8411}, DOI = {10.1016/j.jaut.2017.09.008}, PUBLISHER = {Academic Press}, ADDRESS = {London}, YEAR = {2018}, DATE = {2018}, JOURNAL = {Journal of Autoimmunity}, VOLUME = {86}, PAGES = {51--61}, }
Endnote
%0 Journal Article %A Goeschl, Lisa %A Preglej, Teresa %A Hamminger, Patricia %A Bonelli, Michael %A Andersen, Liisa %A Boucheron, Nicole %A Guelich, Alexandra F. %A Mueller, Lena %A Saferding, Victoria %A Mufazalov, Ilgiz A. %A Hirahara, Kiyoshi %A Seiser, Christian %A Matthias, Patrick %A Penz, Thomas %A Schuster, Michael %A Bock, Christoph %A Waisman, Ari %A Steiner, Guenter %A Ellmeier, Wilfried %+ External Organizations External Organizations External Organizations 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 A T Cell-specific Deletion of HDAC1 Protects Against Experimental Autoimmune Encephalomyelitis : %G eng %U http://hdl.handle.net/21.11116/0000-0000-8438-C %R 10.1016/j.jaut.2017.09.008 %7 2018 %D 2018 %J Journal of Autoimmunity %O J. Autoimmun. %V 86 %& 51 %P 51 - 61 %I Academic Press %C London %@ false
13. Grosser K, Ramasamy P, Dheghani Amirabad A, Schulz MH, Gasparoni G, Simon M, Schrallhammer M: More than the “Killer Trait”: Infection with the Bacterial Endosymbiont Caedibacter taeniospiralis Causes Transcriptomic Modulation in Paramecium Host. Genome Biology and Evolution 2018, 10.
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@article{Grosser2018, TITLE = {More than the “Killer Trait”: {I}nfection with the Bacterial Endosymbiont {C}aedibacter taeniospiralis Causes Transcriptomic Modulation in Paramecium Host}, AUTHOR = {Grosser, Katrin and Ramasamy, Pathmanaban and Dheghani Amirabad, Azim and Schulz, Marcel Holger and Gasparoni, Gilles and Simon, Martin and Schrallhammer, Martina}, LANGUAGE = {eng}, DOI = {10.1093/gbe/evy024}, PUBLISHER = {Oxford Univ. Press}, ADDRESS = {Oxford}, YEAR = {2018}, DATE = {2018}, JOURNAL = {Genome Biology and Evolution}, VOLUME = {10}, NUMBER = {2}, PAGES = {646--656}, }
Endnote
%0 Journal Article %A Grosser, Katrin %A Ramasamy, Pathmanaban %A Dheghani Amirabad, Azim %A Schulz, Marcel Holger %A Gasparoni, Gilles %A Simon, Martin %A Schrallhammer, Martina %+ 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 %T More than the “Killer Trait”: Infection with the Bacterial Endosymbiont Caedibacter taeniospiralis Causes Transcriptomic Modulation in Paramecium Host : %G eng %U http://hdl.handle.net/21.11116/0000-0000-C023-F %R 10.1093/gbe/evy024 %7 2018 %D 2018 %J Genome Biology and Evolution %O GBE Genome Biol Evol %V 10 %N 2 %& 646 %P 646 - 656 %I Oxford Univ. Press %C Oxford
14. Ha Thanh Pham T, Maurer B, Prchal-Murphy M, Grausenburger R, Grundschober E, Javaheri T, Nivarthi H, Boersma A, Kolbe T, Elabd M, Halbritter F, Pencik J, Kazemi Z, Grebien F, Hengstschlaeger M, Kenner L, Kubicek S, Farlik M, Bock C, Valent P, Mueller M, Ruelicke T, Sexl V, Moriggl R: STAT5B(N642H) is a Driver Mutation for T Cell Neoplasia. The Journal of Clinical Investigation 2018, 128.
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@article{Bock_JCI2018, TITLE = {{STAT5B}^({N642H)} is a Driver Mutation for {T} Cell Neoplasia}, AUTHOR = {Ha Thanh Pham, Thi and Maurer, Barbara and Prchal-Murphy, Michaela and Grausenburger, Reinhard and Grundschober, Eva and Javaheri, Tahereh and Nivarthi, Harini and Boersma, Auke and Kolbe, Thomas and Elabd, Mohamed and Halbritter, Florian and Pencik, Jan and Kazemi, Zahra and Grebien, Florian and Hengstschlaeger, Markus and Kenner, Lukas and Kubicek, Stefan and Farlik, Matthias and Bock, Christoph and Valent, Peter and Mueller, Mathias and Ruelicke, Thomas and Sexl, Veronika and Moriggl, Richard}, LANGUAGE = {eng}, ISSN = {0021-9738}, DOI = {10.1172/JCI94509}, PUBLISHER = {American Society for Clinical Investigation}, ADDRESS = {New York, NY}, YEAR = {2018}, DATE = {2018}, JOURNAL = {The Journal of Clinical Investigation}, VOLUME = {128}, NUMBER = {1}, PAGES = {387--401}, }
Endnote
%0 Journal Article %A Ha Thanh Pham, Thi %A Maurer, Barbara %A Prchal-Murphy, Michaela %A Grausenburger, Reinhard %A Grundschober, Eva %A Javaheri, Tahereh %A Nivarthi, Harini %A Boersma, Auke %A Kolbe, Thomas %A Elabd, Mohamed %A Halbritter, Florian %A Pencik, Jan %A Kazemi, Zahra %A Grebien, Florian %A Hengstschlaeger, Markus %A Kenner, Lukas %A Kubicek, Stefan %A Farlik, Matthias %A Bock, Christoph %A Valent, Peter %A Mueller, Mathias %A Ruelicke, Thomas %A Sexl, Veronika %A Moriggl, Richard %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations 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 %T STAT5B(N642H) is a Driver Mutation for T Cell Neoplasia : %G eng %U http://hdl.handle.net/21.11116/0000-0000-2DDC-7 %R 10.1172/JCI94509 %7 2018 %D 2018 %J The Journal of Clinical Investigation %O JCI %V 128 %N 1 %& 387 %P 387 - 401 %I American Society for Clinical Investigation %C New York, NY %@ false
15. Lowe R, Barton C, Jenkins CA, Ernst C, Forman O, Fernandez-Twinn DS, Bock C, Rossiter SJ, Faulkes CG, Ozanne SE, Walter L, Odom DT, Mellersh C, Rakyan VK: Ageing-associated DNA Methylation Dynamics are a Molecular Readout of Lifespan Variation among Mammalian Species. Genome Biology 2018, 19.
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@article{Lowe2018, TITLE = {Ageing-associated {DNA} Methylation Dynamics are a Molecular Readout of Lifespan Variation among Mammalian Species}, AUTHOR = {Lowe, Robert and Barton, Carl and Jenkins, Christopher A. and Ernst, Christina and Forman, Oliver and Fernandez-Twinn, Denise S. and Bock, Christoph and Rossiter, Stephen J. and Faulkes, Chris G. and Ozanne, Susan E. and Walter, Lutz and Odom, Duncan T. and Mellersh, Cathryn and Rakyan, Vardhman K.}, LANGUAGE = {eng}, ISSN = {1465-6906}, DOI = {10.1186/s13059-018-1397-1}, PUBLISHER = {BioMed Central Ltd.}, ADDRESS = {London}, YEAR = {2018}, JOURNAL = {Genome Biology}, VOLUME = {19}, EID = {22}, }
Endnote
%0 Journal Article %A Lowe, Robert %A Barton, Carl %A Jenkins, Christopher A. %A Ernst, Christina %A Forman, Oliver %A Fernandez-Twinn, Denise S. %A Bock, Christoph %A Rossiter, Stephen J. %A Faulkes, Chris G. %A Ozanne, Susan E. %A Walter, Lutz %A Odom, Duncan T. %A Mellersh, Cathryn %A Rakyan, Vardhman K. %+ 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 %T Ageing-associated DNA Methylation Dynamics are a Molecular Readout of Lifespan Variation among Mammalian Species : %G eng %U http://hdl.handle.net/21.11116/0000-0000-C8CF-6 %R 10.1186/s13059-018-1397-1 %7 2018 %D 2018 %J Genome Biology %V 19 %Z sequence number: 22 %I BioMed Central Ltd. %C London %@ false
16. Marschall T, Marz M, Abeel T, Dijkstra L, Dutilh BE, Ghaffaari A, Kersey P, Kloosterman WP, Makinen V, Novak AM, Paten B, Porubsky D, Rivals E, Alkan C, Baaijens JA, De Bakker PIW, Boeva V, Bonnal RJP, Chiaromonte F, Chikhi R, Ciccarelli FD, Cijvat R, Datema E, Van Duijn CM, Eichler EE, Ernst C, Eskin E, Garrison E, El-Kebir M, Klau GW, et al.: Computational Pan-genomics: Status, Promises and Challenges. Briefings in Bioinformatics 2018, 19.
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@article{Marschall2016, TITLE = {Computational Pan-genomics: Status, Promises and Challenges}, AUTHOR = {Marschall, Tobias and Marz, Manja and Abeel, Thomas and Dijkstra, Louis and Dutilh, Bas E. and Ghaffaari, Ali and Kersey, Paul and Kloosterman, Wigard P. and Makinen, Veli and Novak, Adam M. and Paten, Benedict and Porubsky, David and Rivals, Eric and Alkan, Can and Baaijens, Jasmijn A. and De Bakker, Paul I. W. and Boeva, Valentina and Bonnal, Raoul J. P. and Chiaromonte, Francesca and Chikhi, Rayan and Ciccarelli, Francesca D. and Cijvat, Robin and Datema, Erwin and Van Duijn, Cornelia M. and Eichler, Evan E. and Ernst, Corinna and Eskin, Eleazar and Garrison, Erik and El-Kebir, Mohammed and Klau, Gunnar W. and Korbel, Jan O. and Lameijer, Eric-Wubbo and Langmead, Benjamin and Martin, Marcel and Medvedev, Paul and Mu, John C. and Neerincx, Pieter and Ouwens, Klaasjan and Peterlongo, Pierre and Pisanti, Nadia and Rahmann, Sven and Raphael, Ben and Reinert, Knut and de Ridder, Dick and de Ridder, Jeroen and Schlesner, Matthias and Schulz-Trieglaff, Ole and Sanders, Ashley D. and Sheikhizadeh, Siavash and Shneider, Carl and Smit, Sandra and Valenzuela, Daniel and Wang, Jiayin and Wessels, Lodewyk and Zhang, Ying and Guryev, Victor and Vandin, Fabio and Ye, Kai and Schonhuth, Alexander}, LANGUAGE = {eng}, ISSN = {1467-5463}, DOI = {10.1093/bib/bbw089}, PUBLISHER = {Oxford University Press}, ADDRESS = {London}, YEAR = {2018}, DATE = {2018}, JOURNAL = {Briefings in Bioinformatics}, VOLUME = {19}, NUMBER = {1}, PAGES = {118--135}, EID = {bbw089}, }
Endnote
%0 Journal Article %A Marschall, Tobias %A Marz, Manja %A Abeel, Thomas %A Dijkstra, Louis %A Dutilh, Bas E. %A Ghaffaari, Ali %A Kersey, Paul %A Kloosterman, Wigard P. %A Makinen, Veli %A Novak, Adam M. %A Paten, Benedict %A Porubsky, David %A Rivals, Eric %A Alkan, Can %A Baaijens, Jasmijn A. %A De Bakker, Paul I. W. %A Boeva, Valentina %A Bonnal, Raoul J. P. %A Chiaromonte, Francesca %A Chikhi, Rayan %A Ciccarelli, Francesca D. %A Cijvat, Robin %A Datema, Erwin %A Van Duijn, Cornelia M. %A Eichler, Evan E. %A Ernst, Corinna %A Eskin, Eleazar %A Garrison, Erik %A El-Kebir, Mohammed %A Klau, Gunnar W. %A Korbel, Jan O. %A Lameijer, Eric-Wubbo %A Langmead, Benjamin %A Martin, Marcel %A Medvedev, Paul %A Mu, John C. %A Neerincx, Pieter %A Ouwens, Klaasjan %A Peterlongo, Pierre %A Pisanti, Nadia %A Rahmann, Sven %A Raphael, Ben %A Reinert, Knut %A de Ridder, Dick %A de Ridder, Jeroen %A Schlesner, Matthias %A Schulz-Trieglaff, Ole %A Sanders, Ashley D. %A Sheikhizadeh, Siavash %A Shneider, Carl %A Smit, Sandra %A Valenzuela, Daniel %A Wang, Jiayin %A Wessels, Lodewyk %A Zhang, Ying %A Guryev, Victor %A Vandin, Fabio %A Ye, Kai %A Schonhuth, Alexander %+ 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 External Organizations External Organizations External Organizations External Organizations 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 Computational Pan-genomics: Status, Promises and Challenges : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002B-AF03-A %R 10.1093/bib/bbw089 %7 2016-10-21 %D 2018 %J Briefings in Bioinformatics %V 19 %N 1 %& 118 %P 118 - 135 %Z sequence number: bbw089 %I Oxford University Press %C London %@ false
17. Nazarieh M: Understanding Regulatory Mechanisms Underlying Stem Cells Helps to Identify Cancer Biomarkers. Universität des Saarlandes; 2018.
Abstract
Detection of biomarker genes play a crucial role in disease detection and treatment. Bioinformatics offers a variety of approaches for identification of biomarker genes which play key roles in complex diseases. These computational approaches enhance the insight derived from experiments and reduce the efforts of biologists and experimentalists. This is essentially achieved through prioritizing a set of genes with certain attributes. In this thesis, we show that understanding the regulatory mechanisms underlying stem cells helps to identify cancer biomarkers. We got inspired by the regulatory mechanisms of the pluripotency network in mouse embryonic stem cells and formulated the problem where a set of master regulatory genes in regulatory networks is identified with two combinatorial optimization problems namely as minimum dominating set and minimum connected dominating set in weakly and strongly connected components. Then we applied the developed methods to regulatory cancer networks to identify disease-associated genes and anti-cancer drug targets in breast cancer and hepatocellular carcinoma. As not all the nodes in the solutions are critical, we developed a prioritization method to rank a set of candidate genes which are related to a certain disease based on systematic analysis of the genes that are differentially expressed in tumor and normal conditions. Moreover, we demonstrated that the topological features in regulatory networks surrounding differentially expressed genes are highly consistent in terms of using the output of several analysis tools. We compared two randomization strategies for TF-miRNA co-regulatory networks to infer significant network motifs underlying cellular identity. We showed that the edge-type conserving method surpasses the non-conserving method in terms of biological relevance and centrality overlap. We presented several web servers and software packages that are publicly available at no cost. The Cytoscape plugin of minimum connected dominating set identifies a set of key regulatory genes in a user provided regulatory network based on a heuristic approach. The ILP formulations of minimum dominating set and minimum connected dominating set return the optimal solutions for the aforementioned problems. Our source code is publicly available. The web servers TFmiR and TFmiR2 construct disease-, tissue-, process-specific networks for the sets of deregulated genes and miRNAs provided by a user. They highlight topological hotspots and offer detection of three- and four-node FFL motifs as a separate web service for both organisms mouse and human.
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@phdthesis{nazariehphd2017, TITLE = {Understanding Regulatory Mechanisms Underlying Stem Cells Helps to Identify Cancer Biomarkers}, AUTHOR = {Nazarieh, Maryam}, LANGUAGE = {eng}, DOI = {10.22028/D291-27265}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2018}, DATE = {2018}, ABSTRACT = {Detection of biomarker genes play a crucial role in disease detection and treatment. Bioinformatics offers a variety of approaches for identification of biomarker genes which play key roles in complex diseases. These computational approaches enhance the insight derived from experiments and reduce the efforts of biologists and experimentalists. This is essentially achieved through prioritizing a set of genes with certain attributes. In this thesis, we show that understanding the regulatory mechanisms underlying stem cells helps to identify cancer biomarkers. We got inspired by the regulatory mechanisms of the pluripotency network in mouse embryonic stem cells and formulated the problem where a set of master regulatory genes in regulatory networks is identified with two combinatorial optimization problems namely as minimum dominating set and minimum connected dominating set in weakly and strongly connected components. Then we applied the developed methods to regulatory cancer networks to identify disease-associated genes and anti-cancer drug targets in breast cancer and hepatocellular carcinoma. As not all the nodes in the solutions are critical, we developed a prioritization method to rank a set of candidate genes which are related to a certain disease based on systematic analysis of the genes that are differentially expressed in tumor and normal conditions. Moreover, we demonstrated that the topological features in regulatory networks surrounding differentially expressed genes are highly consistent in terms of using the output of several analysis tools. We compared two randomization strategies for TF-miRNA co-regulatory networks to infer significant network motifs underlying cellular identity. We showed that the edge-type conserving method surpasses the non-conserving method in terms of biological relevance and centrality overlap. We presented several web servers and software packages that are publicly available at no cost. The Cytoscape plugin of minimum connected dominating set identifies a set of key regulatory genes in a user provided regulatory network based on a heuristic approach. The ILP formulations of minimum dominating set and minimum connected dominating set return the optimal solutions for the aforementioned problems. Our source code is publicly available. The web servers TFmiR and TFmiR2 construct disease-, tissue-, process-specific networks for the sets of deregulated genes and miRNAs provided by a user. They highlight topological hotspots and offer detection of three- and four-node FFL motifs as a separate web service for both organisms mouse and human.}, }
Endnote
%0 Thesis %A Nazarieh, Maryam %Y Helms, Volker %A referee: 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 Understanding Regulatory Mechanisms Underlying Stem Cells Helps to Identify Cancer Biomarkers : %G eng %U http://hdl.handle.net/21.11116/0000-0001-9D69-9 %R 10.22028/D291-27265 %I Universität des Saarlandes %C Saarbrücken %D 2018 %P 139 p. %V phd %9 phd %X Detection of biomarker genes play a crucial role in disease detection and treatment. Bioinformatics offers a variety of approaches for identification of biomarker genes which play key roles in complex diseases. These computational approaches enhance the insight derived from experiments and reduce the efforts of biologists and experimentalists. This is essentially achieved through prioritizing a set of genes with certain attributes. In this thesis, we show that understanding the regulatory mechanisms underlying stem cells helps to identify cancer biomarkers. We got inspired by the regulatory mechanisms of the pluripotency network in mouse embryonic stem cells and formulated the problem where a set of master regulatory genes in regulatory networks is identified with two combinatorial optimization problems namely as minimum dominating set and minimum connected dominating set in weakly and strongly connected components. Then we applied the developed methods to regulatory cancer networks to identify disease-associated genes and anti-cancer drug targets in breast cancer and hepatocellular carcinoma. As not all the nodes in the solutions are critical, we developed a prioritization method to rank a set of candidate genes which are related to a certain disease based on systematic analysis of the genes that are differentially expressed in tumor and normal conditions. Moreover, we demonstrated that the topological features in regulatory networks surrounding differentially expressed genes are highly consistent in terms of using the output of several analysis tools. We compared two randomization strategies for TF-miRNA co-regulatory networks to infer significant network motifs underlying cellular identity. We showed that the edge-type conserving method surpasses the non-conserving method in terms of biological relevance and centrality overlap. We presented several web servers and software packages that are publicly available at no cost. The Cytoscape plugin of minimum connected dominating set identifies a set of key regulatory genes in a user provided regulatory network based on a heuristic approach. The ILP formulations of minimum dominating set and minimum connected dominating set return the optimal solutions for the aforementioned problems. Our source code is publicly available. The web servers TFmiR and TFmiR2 construct disease-, tissue-, process-specific networks for the sets of deregulated genes and miRNAs provided by a user. They highlight topological hotspots and offer detection of three- and four-node FFL motifs as a separate web service for both organisms mouse and human. %U https://publikationen.sulb.uni-saarland.de/handle/20.500.11880/27104
18. Pan W-H, Sommer F, Falk-Paulsen M, Ulas T, Best P, Fazio A, Kachroo P, Luzius A, Jentzsch M, Rehman A, Müller F, Lengauer T, Walter J, Kuenzel S, Baines JF, Schreiber S, Franke A, Schultze JL, Backhed F, Rosenstiel P: Exposure to the Gut Microbiota Drives Distinct Methylome and Transcriptome Changes in Intestinal Epithelial Cells during Postnatal Development. Genome Medicine 2018, 10.
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@article{Pan2018, TITLE = {Exposure to the Gut Microbiota Drives Distinct Methylome and Transcriptome Changes in Intestinal Epithelial Cells during Postnatal Development}, AUTHOR = {Pan, Wei-Hung and Sommer, Felix and Falk-Paulsen, Maren and Ulas, Thomas and Best, Philipp and Fazio, Antonella and Kachroo, Priyadarshini and Luzius, Anne and Jentzsch, Marlene and Rehman, Ateequr and M{\"u}ller, Fabian and Lengauer, Thomas and Walter, Joern and Kuenzel, Sven and Baines, John F. and Schreiber, Stefan and Franke, Andre and Schultze, Joachim L. and Backhed, Fredrik and Rosenstiel, Philip}, LANGUAGE = {eng}, DOI = {10.1186/s13073-018-0534-5}, PUBLISHER = {BioMed Central}, ADDRESS = {London}, YEAR = {2018}, JOURNAL = {Genome Medicine}, VOLUME = {10}, EID = {27}, }
Endnote
%0 Journal Article %A Pan, Wei-Hung %A Sommer, Felix %A Falk-Paulsen, Maren %A Ulas, Thomas %A Best, Philipp %A Fazio, Antonella %A Kachroo, Priyadarshini %A Luzius, Anne %A Jentzsch, Marlene %A Rehman, Ateequr %A Müller, Fabian %A Lengauer, Thomas %A Walter, Joern %A Kuenzel, Sven %A Baines, John F. %A Schreiber, Stefan %A Franke, Andre %A Schultze, Joachim L. %A Backhed, Fredrik %A Rosenstiel, Philip %+ 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 %T Exposure to the Gut Microbiota Drives Distinct Methylome and Transcriptome Changes in Intestinal Epithelial Cells during Postnatal Development : %G eng %U http://hdl.handle.net/21.11116/0000-0001-37F8-A %R 10.1186/s13073-018-0534-5 %7 2018 %D 2018 %J Genome Medicine %V 10 %Z sequence number: 27 %I BioMed Central %C London
19. Pirritano M, Goetz U, Karunanithi S, Nordstroem K, Schulz MH, Simon M: Environmental Temperature Controls Accumulation of Transacting siRNAs Involved in Heterochromatin Formation. Genes 2018, 9.
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@article{Pirritano2018, TITLE = {Environmental Temperature Controls Accumulation of Transacting {siRNAs} Involved in Heterochromatin Formation}, AUTHOR = {Pirritano, Marcello and Goetz, Ulrike and Karunanithi, Sivarajan and Nordstroem, Karl and Schulz, Marcel H. and Simon, Martin}, LANGUAGE = {eng}, ISSN = {2073-4425}, DOI = {10.3390/genes9020117}, PUBLISHER = {MPDI}, ADDRESS = {Basel}, YEAR = {2018}, JOURNAL = {Genes}, VOLUME = {9}, NUMBER = {2}, EID = {117}, }
Endnote
%0 Journal Article %A Pirritano, Marcello %A Goetz, Ulrike %A Karunanithi, Sivarajan %A Nordstroem, Karl %A Schulz, Marcel H. %A Simon, Martin %+ 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 Environmental Temperature Controls Accumulation of Transacting siRNAs Involved in Heterochromatin Formation : %G eng %U http://hdl.handle.net/21.11116/0000-0001-1F9E-C %R 10.3390/genes9020117 %2 PMC5852613 %7 2018 %D 2018 %J Genes %V 9 %N 2 %Z sequence number: 117 %I MPDI %C Basel %@ false
20. Simovski B, Kanduri C, Gundersen S, Titov D, Domanska D, Bock C, Bossini-Castillo L, Chikina M, Favorov A, Layer RM, Mironov AA, Quinlan AR, Sheffield NC, Trynka G, Sandve GK: Coloc-stats: A Unified Web Interface to Perform Colocalization Analysis of Genomic Features. Nucleic Acids Research 2018, 46(Web Server issue).
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@article{Simovski_2018, TITLE = {Coloc-stats: A Unified Web Interface to Perform Colocalization Analysis of Genomic Features}, AUTHOR = {Simovski, Boris and Kanduri, Chakravarthi and Gundersen, Sveinung and Titov, Dmytro and Domanska, Diana and Bock, Christoph and Bossini-Castillo, Lara and Chikina, Maria and Favorov, Alexander and Layer, Ryan M. and Mironov, Andrey A. and Quinlan, Aaron R. and Sheffield, Nathan C. and Trynka, Gosia and Sandve, Geir K.}, LANGUAGE = {eng}, ISSN = {0301-5610}, DOI = {10.1093/nar/gky474}, PUBLISHER = {Oxford University Press}, ADDRESS = {Oxford, UK}, YEAR = {2018}, DATE = {2018}, JOURNAL = {Nucleic Acids Research}, VOLUME = {46}, NUMBER = {Web Server issue}, PAGES = {W186--W193}, }
Endnote
%0 Journal Article %A Simovski, Boris %A Kanduri, Chakravarthi %A Gundersen, Sveinung %A Titov, Dmytro %A Domanska, Diana %A Bock, Christoph %A Bossini-Castillo, Lara %A Chikina, Maria %A Favorov, Alexander %A Layer, Ryan M. %A Mironov, Andrey A. %A Quinlan, Aaron R. %A Sheffield, Nathan C. %A Trynka, Gosia %A Sandve, Geir K. %+ 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 %T Coloc-stats: A Unified Web Interface to Perform Colocalization Analysis of Genomic Features : %G eng %U http://hdl.handle.net/21.11116/0000-0001-E5C6-D %R 10.1093/nar/gky474 %7 2018 %D 2018 %J Nucleic Acids Research %O Nucleic Acids Res. %V 46 %N Web Server issue %& W186 %P W186 - W193 %I Oxford University Press %C Oxford, UK %@ false