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1. Ahmad M, Helms V, Kalinina OV, Lengauer T: Elucidating the Energetic Contributions to the Binding Free Energy. The Journal of Chemical Physics 2017, 146.
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@article{Ahmad2017, TITLE = {Elucidating the Energetic Contributions to the Binding Free Energy}, AUTHOR = {Ahmad, Mazen and Helms, Volkhard and Kalinina, Olga V. and Lengauer, Thomas}, LANGUAGE = {eng}, ISSN = {0021-9606}, DOI = {10.1063/1.4973349}, PUBLISHER = {American Institute of Physics}, ADDRESS = {Woodbury, N.Y.}, YEAR = {2017}, MARGINALMARK = {$\bullet$}, DATE = {2017}, JOURNAL = {The Journal of Chemical Physics}, VOLUME = {146}, NUMBER = {1}, EID = {014105}, }
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%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 Elucidating the Energetic Contributions to the Binding Free Energy : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002C-3A74-2 %R 10.1063/1.4973349 %7 2017 %D 2017 %J The Journal of Chemical Physics %O J. Chem. Phys. %V 146 %N 1 %Z sequence number: 014105 %I American Institute of Physics %C Woodbury, N.Y. %@ false
2. Albrecht F, List M, Bock C, Lengauer T: DeepBlueR: Large-scale Epigenomic Analysis in R. Bioinformatics 2017.
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@article{AlbrechtBioinformatics2017, TITLE = {{DeepBlueR}: {L}arge-scale Epigenomic Analysis in {R}}, AUTHOR = {Albrecht, Felipe and List, Markus and Bock, Christoph and Lengauer, Thomas}, LANGUAGE = {eng}, ISSN = {1367-4803}, DOI = {10.1093/bioinformatics/btx099}, PUBLISHER = {Oxford University Press}, ADDRESS = {Oxford}, YEAR = {2017}, MARGINALMARK = {$\bullet$}, JOURNAL = {Bioinformatics}, EID = {btx099}, }
Endnote
%0 Journal Article %A Albrecht, Felipe %A List, Markus %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 %T DeepBlueR: Large-scale Epigenomic Analysis in R : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002C-8AB4-4 %R 10.1093/bioinformatics/btx099 %7 2017-02-22 %D 2017 %8 22.02.2017 %J Bioinformatics %Z sequence number: btx099 %I Oxford University Press %C Oxford %@ false
3. Almeida D, Skov I, Silva A, Vandin F, Tan Q, Röttger R, Baumbach J: Efficient Detection of Differentially Methylated Regions using DiMmeR. Bioinformatics 2017, 33.
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@article{Almeida2017, TITLE = {Efficient Detection of Differentially Methylated Regions using {DiMmeR}}, AUTHOR = {Almeida, Diogo and Skov, Ida and Silva, Artur and Vandin, Fabio and Tan, Qihua and R{\"o}ttger, Richard and Baumbach, Jan}, LANGUAGE = {eng}, ISSN = {1367-4803}, DOI = {10.1093/bioinformatics/btw657}, PUBLISHER = {Oxford University Press}, ADDRESS = {Oxford}, YEAR = {2017}, MARGINALMARK = {$\bullet$}, DATE = {2017}, JOURNAL = {Bioinformatics}, VOLUME = {33}, NUMBER = {4}, PAGES = {549--551}, }
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%0 Journal Article %A Almeida, Diogo %A Skov, Ida %A Silva, Artur %A Vandin, Fabio %A Tan, Qihua %A Röttger, Richard %A Baumbach, Jan %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Efficient Detection of Differentially Methylated Regions using DiMmeR : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002C-ECA5-7 %R 10.1093/bioinformatics/btw657 %7 2016 %D 2017 %J Bioinformatics %V 33 %N 4 %& 549 %P 549 - 551 %I Oxford University Press %C Oxford %@ false
4. Bader J, Däumer M, Schöni-Affolter F, Böni J, Gorgievski-Hrisoho M, Martinetti G, Thielen A, Klimkait T: Therapeutic Immune Recovery and Reduction of CXCR4-Tropic HIV-1. Clinical Infectious Diseases 2017, 64.
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@article{Bader2017, TITLE = {Therapeutic Immune Recovery and Reduction of {CXCR4}-Tropic {HIV}-1}, AUTHOR = {Bader, Jo{\"e}lle and D{\"a}umer, Martin and Sch{\"o}ni-Affolter, Franziska and B{\"o}ni, J{\"u}rg and Gorgievski-Hrisoho, Meri and Martinetti, Gladys and Thielen, Alexander and Klimkait, Thomas}, LANGUAGE = {eng}, ISSN = {1058-4838}, DOI = {10.1093/cid/ciw737}, PUBLISHER = {The University of Chicago Press}, ADDRESS = {Chicago, IL}, YEAR = {2017}, MARGINALMARK = {$\bullet$}, DATE = {2017}, JOURNAL = {Clinical Infectious Diseases}, VOLUME = {64}, NUMBER = {3}, PAGES = {295--300}, }
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%0 Journal Article %A Bader, Joëlle %A Däumer, Martin %A Schöni-Affolter, Franziska %A Böni, Jürg %A Gorgievski-Hrisoho, Meri %A Martinetti, Gladys %A Thielen, Alexander %A Klimkait, Thomas %+ 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 Therapeutic Immune Recovery and Reduction of CXCR4-Tropic HIV-1 : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002C-ECAE-6 %R 10.1093/cid/ciw737 %7 2016 %D 2017 %J Clinical Infectious Diseases %V 64 %N 3 %& 295 %P 295 - 300 %I The University of Chicago Press %C Chicago, IL %@ false
5. Batra R, Alcaraz N, Gitzhofer K, Pauling J, Ditzel HJ, Hellmuth M, Baumbach J, List M: On the Performance of De Novo Pathway Enrichment. njp Systems Biology and Applications 2017, 3.
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@article{Baumbachnjp2016, TITLE = {On the Performance of De Novo Pathway Enrichment}, AUTHOR = {Batra, Richa and Alcaraz, Nicolas and Gitzhofer, Kevin and Pauling, Josch and Ditzel, Henrik J. and Hellmuth, Marc and Baumbach, Jan and List, Markus}, LANGUAGE = {eng}, DOI = {10.1038/s41540-017-0007-2}, PUBLISHER = {Nature Publishing Group}, ADDRESS = {London}, YEAR = {2017}, MARGINALMARK = {$\bullet$}, JOURNAL = {njp Systems Biology and Applications}, VOLUME = {3}, PAGES = {1--8}, EID = {6}, }
Endnote
%0 Journal Article %A Batra, Richa %A Alcaraz, Nicolas %A Gitzhofer, Kevin %A Pauling, Josch %A Ditzel, Henrik J. %A Hellmuth, Marc %A Baumbach, Jan %A List, Markus %+ 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 On the Performance of De Novo Pathway Enrichment : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002C-2039-6 %R 10.1038/s41540-017-0007-2 %7 2017 %D 2017 %J njp Systems Biology and Applications %V 3 %& 1 %P 1 - 8 %Z sequence number: 6 %I Nature Publishing Group %C London
6. Busch CJ-L, Hendrikx T, Weismann D, Jäckel S, Walenbergh SMA, Rendeiro AF, Weißer J, Puhm F, Hladik A, Göderle L, Papac-Milicevic N, Haas G, Millischer V, Subramaniam S, Knapp S, Bennett KL, Bock C, Reinhardt C, Shiri-Sverdlov R, Binder CJ: Malondialdehyde Epitopes Are Sterile Mediators of Hepatic Inflammation in Hypercholesterolemic Mice. Hepatology 2017, 65.
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@article{Busch2017, TITLE = {Malondialdehyde Epitopes Are Sterile Mediators of Hepatic Inflammation in Hypercholesterolemic Mice}, AUTHOR = {Busch, Clara Jana-Lui and Hendrikx, Tim and Weismann, David and J{\"a}ckel, Sven and Walenbergh, Sofie M. A. and Rendeiro, Andr{\'e} F. and Wei{\ss}er, Juliane and Puhm, Florian and Hladik, Anastasiya and G{\"o}derle, Laura and Papac-Milicevic, Nikolina and Haas, Gerald and Millischer, Vincent and Subramaniam, Saravanan and Knapp, Sylvia and Bennett, Keiryn L. and Bock, Christoph and Reinhardt, Christoph and Shiri-Sverdlov, Ronit and Binder, Christoph J.}, LANGUAGE = {eng}, ISSN = {0270-9139}, DOI = {10.1002/hep.28970}, PUBLISHER = {AASLD}, ADDRESS = {Alexandria, VA}, YEAR = {2017}, MARGINALMARK = {$\bullet$}, JOURNAL = {Hepatology}, VOLUME = {65}, NUMBER = {4}, PAGES = {1181--1195}, }
Endnote
%0 Journal Article %A Busch, Clara Jana-Lui %A Hendrikx, Tim %A Weismann, David %A Jäckel, Sven %A Walenbergh, Sofie M. A. %A Rendeiro, André F. %A Weißer, Juliane %A Puhm, Florian %A Hladik, Anastasiya %A Göderle, Laura %A Papac-Milicevic, Nikolina %A Haas, Gerald %A Millischer, Vincent %A Subramaniam, Saravanan %A Knapp, Sylvia %A Bennett, Keiryn L. %A Bock, Christoph %A Reinhardt, Christoph %A Shiri-Sverdlov, Ronit %A Binder, Christoph J. %+ External Organizations External Organizations External Organizations External Organizations 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 Malondialdehyde Epitopes Are Sterile Mediators of Hepatic Inflammation in Hypercholesterolemic Mice : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002C-576B-C %R 10.1002/hep.28970 %7 2017 %D 2017 %J Hepatology %V 65 %N 4 %& 1181 %P 1181 - 1195 %I AASLD %C Alexandria, VA %@ false
7. Caskey M, Schoofs T, Gruell H, Settler A, Karagounis T, Kreider EF, Murrell B, Pfeifer N, Nogueira L, Oliveira TY, Learn GH, Cohen YZ, Lehmann C, Gillor D, Shimeliovich I, Unson-O’Brien C, Weiland D, Robles A, Kümmerle T, Wyen C, Levin R, Witmer-Pack M, Eren K, Ignacio C, Kiss S, Jr APW, Mouquet H, Zingman BS, Gulick RM, Keler T, et al.: Antibody 10-1074 Suppresses Viremia in HIV-1-infected Individuals. Nature Medicine 2017, 23.
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@article{Pfeifernature2017, TITLE = {Antibody 10-1074 Suppresses Viremia in {HIV}-1-infected Individuals}, AUTHOR = {Caskey, Marina and Schoofs, Till and Gruell, Henning and Settler, Allison and Karagounis, Theodora and Kreider, Edward F and Murrell, Ben and Pfeifer, Nico and Nogueira, Lilian and Oliveira, Thiago Y and Learn, Gerald H and Cohen, Yehuda Z and Lehmann, Clara and Gillor, Daniel and Shimeliovich, Irina and Unson-O{\textquoteright}Brien, Cecilia and Weiland, Daniela and Robles, Alexander and K{\"u}mmerle, Tim and Wyen, Christoph and Levin, Rebeka and Witmer-Pack, Maggi and Eren, Kemal and Ignacio, Caroline and Kiss, Szilard and Jr, Anthony P West and Mouquet, Hugo and Zingman, Barry S and Gulick, Roy M and Keler, Tibor and Bjorkman, Pamela J and Seaman, Michael S and Hahn, Beatrice H and F{\"a}tkenheuer, Gerd and Schlesinger, Sarah J and Nussenzweig, Michel C and Klein, Florian}, LANGUAGE = {eng}, ISSN = {1078-8956}, DOI = {10.1038/nm.4268}, PUBLISHER = {Nature Pub. Co.}, ADDRESS = {New York, NY}, YEAR = {2017}, MARGINALMARK = {$\bullet$}, DATE = {2017}, JOURNAL = {Nature Medicine}, VOLUME = {23}, NUMBER = {2}, PAGES = {185--191}, }
Endnote
%0 Journal Article %A Caskey, Marina %A Schoofs, Till %A Gruell, Henning %A Settler, Allison %A Karagounis, Theodora %A Kreider, Edward F %A Murrell, Ben %A Pfeifer, Nico %A Nogueira, Lilian %A Oliveira, Thiago Y %A Learn, Gerald H %A Cohen, Yehuda Z %A Lehmann, Clara %A Gillor, Daniel %A Shimeliovich, Irina %A Unson-O’Brien, Cecilia %A Weiland, Daniela %A Robles, Alexander %A Kümmerle, Tim %A Wyen, Christoph %A Levin, Rebeka %A Witmer-Pack, Maggi %A Eren, Kemal %A Ignacio, Caroline %A Kiss, Szilard %A Jr, Anthony P West %A Mouquet, Hugo %A Zingman, Barry S %A Gulick, Roy M %A Keler, Tibor %A Bjorkman, Pamela J %A Seaman, Michael S %A Hahn, Beatrice H %A Fätkenheuer, Gerd %A Schlesinger, Sarah J %A Nussenzweig, Michel C %A Klein, Florian %+ 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 Antibody 10-1074 Suppresses Viremia in HIV-1-infected Individuals : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002C-7F0C-8 %R 10.1038/nm.4268 %7 2017-01-16 %D 2017 %J Nature Medicine %O Nat. Med. %V 23 %N 2 %& 185 %P 185 - 191 %I Nature Pub. Co. %C New York, NY %@ false
8. Datlinger P, Rendeiro AF, Schmidl C, Krausgruber T, Traxler P, Klughammer J, Schuster LC, Kuchler A, Alpar D, Bock C: Pooled CRISPR Screening with Single-cell Transcriptome Readout. Nature Methods 2017, 14.
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@article{Bocknature2017, TITLE = {Pooled {CRISPR} Screening with Single-cell Transcriptome Readout}, AUTHOR = {Datlinger, Paul and Rendeiro, Andr{\'e} F and Schmidl, Christian and Krausgruber, Thomas and Traxler, Peter and Klughammer, Johanna and Schuster, Linda C and Kuchler, Amelie and Alpar, Donat and Bock, Christoph}, LANGUAGE = {eng}, ISSN = {1548-7091}, DOI = {10.1038/nmeth.4177}, PUBLISHER = {Nature Pub. Group}, ADDRESS = {New York, NY}, YEAR = {2017}, MARGINALMARK = {$\bullet$}, DATE = {2017}, JOURNAL = {Nature Methods}, VOLUME = {14}, NUMBER = {3}, PAGES = {297--301}, }
Endnote
%0 Journal Article %A Datlinger, Paul %A Rendeiro, André F %A Schmidl, Christian %A Krausgruber, Thomas %A Traxler, Peter %A Klughammer, Johanna %A Schuster, Linda C %A Kuchler, Amelie %A Alpar, Donat %A Bock, Christoph %+ 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 %T Pooled CRISPR Screening with Single-cell Transcriptome Readout : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002C-532B-2 %R 10.1038/nmeth.4177 %7 2017 %D 2017 %J Nature Methods %O Nature methods %V 14 %N 3 %& 297 %P 297 - 301 %I Nature Pub. Group %C New York, NY %@ false
9. Ebler J, Schönhuth A, Marschall T: Genotyping of Inversions and Tandem Duplications. Bioinformatics 2017.
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@article{Marshallbio17, TITLE = {Genotyping of Inversions and Tandem Duplications}, AUTHOR = {Ebler, Jana and Sch{\"o}nhuth, Alexander and Marschall, Tobias}, LANGUAGE = {eng}, ISSN = {1367-4803}, DOI = {10.1093/bioinformatics/btx020}, PUBLISHER = {Oxford University Press}, ADDRESS = {Oxford}, YEAR = {2017}, MARGINALMARK = {$\bullet$}, JOURNAL = {Bioinformatics}, EID = {btx020}, }
Endnote
%0 Journal Article %A Ebler, Jana %A Schönhuth, Alexander %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 Genotyping of Inversions and Tandem Duplications : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002C-468F-7 %R 10.1093/bioinformatics/btx020 %7 2017-02-07 %D 2017 %8 07.02.2017 %J Bioinformatics %Z sequence number: btx020 %I Oxford University Press %C Oxford %@ false
10. Selecting Optimal Minimum Spanning Trees that Share a Topological Correspondence with Phylogenetic Trees [http://arxiv.org/abs/1701.02844]
(arXiv: 1701.02844)
Abstract
Choi et. al (2011) introduced a minimum spanning tree (MST)-based method called CLGrouping, for constructing tree-structured probabilistic graphical models, a statistical framework that is commonly used for inferring phylogenetic trees. While CLGrouping works correctly if there is a unique MST, we observe an indeterminacy in the method in the case that there are multiple MSTs. In this work we remove this indeterminacy by introducing so-called vertex-ranked MSTs. We note that the effectiveness of CLGrouping is inversely related to the number of leaves in the MST. This motivates the problem of finding a vertex-ranked MST with the minimum number of leaves (MLVRMST). We provide a polynomial time algorithm for the MLVRMST problem, and prove its correctness for graphs whose edges are weighted with tree-additive distances.
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@online{Kalaghatgi2017, TITLE = {Selecting Optimal Minimum Spanning Trees that Share a Topological Correspondence with Phylogenetic Trees}, AUTHOR = {Kalaghatgi, Prabhav and Lengauer, Thomas}, LANGUAGE = {eng}, URL = {http://arxiv.org/abs/1701.02844}, EPRINT = {1701.02844}, EPRINTTYPE = {arXiv}, YEAR = {2017}, MARGINALMARK = {$\bullet$}, ABSTRACT = {Choi et. al (2011) introduced a minimum spanning tree (MST)-based method called CLGrouping, for constructing tree-structured probabilistic graphical models, a statistical framework that is commonly used for inferring phylogenetic trees. While CLGrouping works correctly if there is a unique MST, we observe an indeterminacy in the method in the case that there are multiple MSTs. In this work we remove this indeterminacy by introducing so-called vertex-ranked MSTs. We note that the effectiveness of CLGrouping is inversely related to the number of leaves in the MST. This motivates the problem of finding a vertex-ranked MST with the minimum number of leaves (MLVRMST). We provide a polynomial time algorithm for the MLVRMST problem, and prove its correctness for graphs whose edges are weighted with tree-additive distances.}, }
Endnote
%0 Report %A Kalaghatgi, Prabhav %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 Selecting Optimal Minimum Spanning Trees that Share a Topological Correspondence with Phylogenetic Trees : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002C-3E81-2 %U http://arxiv.org/abs/1701.02844 %D 2017 %X Choi et. al (2011) introduced a minimum spanning tree (MST)-based method called CLGrouping, for constructing tree-structured probabilistic graphical models, a statistical framework that is commonly used for inferring phylogenetic trees. While CLGrouping works correctly if there is a unique MST, we observe an indeterminacy in the method in the case that there are multiple MSTs. In this work we remove this indeterminacy by introducing so-called vertex-ranked MSTs. We note that the effectiveness of CLGrouping is inversely related to the number of leaves in the MST. This motivates the problem of finding a vertex-ranked MST with the minimum number of leaves (MLVRMST). We provide a polynomial time algorithm for the MLVRMST problem, and prove its correctness for graphs whose edges are weighted with tree-additive distances. %K Mathematics, Combinatorics, math.CO,Computer Science, Data Structures and Algorithms, cs.DS
11. Knops E, Schübel N, Heger E, Neumann-Fraune M, Kaiser R, Inden S, Kalaghatgi P, Sierra S: HCV Resistance Profile Evolution in a GT1b, DAA-Naive Patient Before, On, and After Failing Triple DAA Therapy. Clinical Gastroenterology and Hepatology 2017, 15.
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@article{Knops2017, TITLE = {{HCV} Resistance Profile Evolution in a {GT1b}, {DAA}-Naive Patient Before, On, and After Failing Triple {DAA} Therapy}, AUTHOR = {Knops, Elena and Sch{\"u}bel, Niels and Heger, Eva and Neumann-Fraune, Maria and Kaiser, Rolf and Inden, Stephanie and Kalaghatgi, Prabhav and Sierra, Saleta}, LANGUAGE = {eng}, DOI = {10.1016/j.cgh.2016.09.139}, PUBLISHER = {Elsevier}, ADDRESS = {Amsterdam}, YEAR = {2017}, MARGINALMARK = {$\bullet$}, DATE = {2017}, JOURNAL = {Clinical Gastroenterology and Hepatology}, VOLUME = {15}, NUMBER = {2}, PAGES = {307--309}, }
Endnote
%0 Journal Article %A Knops, Elena %A Schübel, Niels %A Heger, Eva %A Neumann-Fraune, Maria %A Kaiser, Rolf %A Inden, Stephanie %A Kalaghatgi, Prabhav %A Sierra, Saleta %+ 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 HCV Resistance Profile Evolution in a GT1b, DAA-Naive Patient Before, On, and After Failing Triple DAA Therapy : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002C-ECB2-B %R 10.1016/j.cgh.2016.09.139 %7 2017 %D 2017 %J Clinical Gastroenterology and Hepatology %V 15 %N 2 %& 307 %P 307 - 309 %I Elsevier %C Amsterdam
12. Li J, Casteels T, Frogne T, Ingvorsen C, Honoré C, Courtney M, Huber KVM, Schmitner N, Kimmel RA, Romanov RA, Sturtzel C, Lardeau C-H, Klughammer J, Farlik M, Sdelci S, Vieira A, Avolio F, Briand F, Baburin I, Májek P, Pauler FM, Penz T, Stukalov A, Gridling M, Parapatics K, Barbieux C, Berishvili E, Spittler A, Colinge J, Bennett KL, et al.: Artemisinins Target GABA A Receptor Signaling and Impair α Cell Identity. Cell 2017, 168.
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@article{Li2017, TITLE = {Artemisinins Target {GABA$_{\mathrm A}$} Receptor Signaling and Impair $\alpha$ Cell Identity}, AUTHOR = {Li, Jin and Casteels, Tamara and Frogne, Thomas and Ingvorsen, Camilla and Honor{\'e}, Christian and Courtney, Monica and Huber, Kilian V. M. and Schmitner, Nicole and Kimmel, Robin A. and Romanov, Roman A. and Sturtzel, Caterina and Lardeau, Charles-Hugues and Klughammer, Johanna and Farlik, Matthias and Sdelci, Sara and Vieira, Andhira and Avolio, Fabio and Briand, Fran{\c c}ois and Baburin, Igor and M{\'a}jek, Peter and Pauler, Florian M. and Penz, Thomas and Stukalov, Alexey and Gridling, Manuela and Parapatics, Katja and Barbieux, Charlotte and Berishvili, Ekaterine and Spittler, Andreas and Colinge, Jacques and Bennett, Keiryn L. and Hering, Steffen and Sulpice, Thierry and Bock, Christoph and Distel, Martin and Harkany, Tibor and Meyer, Dirk and Superti-Furga, Giulio and Collombat, Patrick and Hecksher-S{\o}rensen, Jacob and Kubicek, Stefan}, LANGUAGE = {eng}, ISSN = {0092-8674}, DOI = {10.1016/j.cell.2016.11.010}, PUBLISHER = {Elsevier}, ADDRESS = {Amsterdam}, YEAR = {2017}, MARGINALMARK = {$\bullet$}, DATE = {2017}, JOURNAL = {Cell}, VOLUME = {168}, NUMBER = {1-2}, PAGES = {86--100}, EID = {e15}, }
Endnote
%0 Journal Article %A Li, Jin %A Casteels, Tamara %A Frogne, Thomas %A Ingvorsen, Camilla %A Honoré, Christian %A Courtney, Monica %A Huber, Kilian V. M. %A Schmitner, Nicole %A Kimmel, Robin A. %A Romanov, Roman A. %A Sturtzel, Caterina %A Lardeau, Charles-Hugues %A Klughammer, Johanna %A Farlik, Matthias %A Sdelci, Sara %A Vieira, Andhira %A Avolio, Fabio %A Briand, François %A Baburin, Igor %A Májek, Peter %A Pauler, Florian M. %A Penz, Thomas %A Stukalov, Alexey %A Gridling, Manuela %A Parapatics, Katja %A Barbieux, Charlotte %A Berishvili, Ekaterine %A Spittler, Andreas %A Colinge, Jacques %A Bennett, Keiryn L. %A Hering, Steffen %A Sulpice, Thierry %A Bock, Christoph %A Distel, Martin %A Harkany, Tibor %A Meyer, Dirk %A Superti-Furga, Giulio %A Collombat, Patrick %A Hecksher-Sørensen, Jacob %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 External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations 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 %T Artemisinins Target GABA A Receptor Signaling and Impair α Cell Identity : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002C-5C72-1 %2 PMC5236063 %R 10.1016/j.cell.2016.11.010 %7 2017 %D 2017 %J Cell %V 168 %N 1-2 %& 86 %P 86 - 100 %Z sequence number: e15 %I Elsevier %C Amsterdam %@ false
13. List M, Elnegaard MP, Schmidt S, Christiansen H, Tan Q, Mollenhauer J, Baumbach J: Efficient Management of High-Throughput Screening Libraries with SAVANAH. Journal of Biomolecular Screening 2017, 22.
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@article{List2016b, TITLE = {Efficient Management of High-Throughput Screening Libraries with {SAVANAH}}, AUTHOR = {List, Markus and Elnegaard, Marlene Pedersen and Schmidt, Steffen and Christiansen, Helle and Tan, Qihua and Mollenhauer, Jan and Baumbach, Jan}, LANGUAGE = {eng}, ISSN = {1087-0571}, DOI = {10.1177/1087057116673607}, PUBLISHER = {Sage Publications, Inc.}, ADDRESS = {Larchmont, NY}, YEAR = {2017}, MARGINALMARK = {$\bullet$}, DATE = {2017}, JOURNAL = {Journal of Biomolecular Screening}, VOLUME = {22}, NUMBER = {2}, PAGES = {196--202}, }
Endnote
%0 Journal Article %A List, Markus %A Elnegaard, Marlene Pedersen %A Schmidt, Steffen %A Christiansen, Helle %A Tan, Qihua %A Mollenhauer, Jan %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 Efficient Management of High-Throughput Screening Libraries with SAVANAH : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002C-202F-D %R 10.1177/1087057116673607 %7 2016-10-11 %D 2017 %J Journal of Biomolecular Screening %V 22 %N 2 %& 196 %P 196 - 202 %I Sage Publications, Inc. %C Larchmont, NY %@ false
14. List M, Ebert P, Albrecht F: Ten Simple Rules for Developing Usable Software in Computational Biology. PLoS Computational Biology 2017, 13.
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@article{ListPloSCompBiol2016, TITLE = {Ten Simple Rules for Developing Usable Software in Computational Biology}, AUTHOR = {List, Markus and Ebert, Peter and Albrecht, Felipe}, LANGUAGE = {eng}, ISSN = {1553-734X}, DOI = {10.1371/journal.pcbi.1005265}, PUBLISHER = {Public Library of Science}, ADDRESS = {San Francisco, CA}, YEAR = {2017}, MARGINALMARK = {$\bullet$}, JOURNAL = {PLoS Computational Biology}, VOLUME = {13}, NUMBER = {1}, EID = {e1005265}, }
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%0 Journal Article %A List, Markus %A Ebert, Peter %A Albrecht, Felipe %+ 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 Ten Simple Rules for Developing Usable Software in Computational Biology : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002C-203B-2 %R 10.1371/journal.pcbi.1005265 %7 2017-01-05 %D 2017 %8 05.01.2017 %J PLoS Computational Biology %V 13 %N 1 %Z sequence number: e1005265 %I Public Library of Science %C San Francisco, CA %@ false
15. Nikumbh S, Pfeifer N: Genetic Sequence-based Prediction of Long-range Chromatin Interactions Suggests a Potential Role of Short Tandem Repeat Sequences in Genome Organization. BMC Bioinformatics 2017, 18.
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@article{Nikumbh2017, TITLE = {Genetic Sequence-based Prediction of Long-range Chromatin Interactions Suggests a Potential Role of Short Tandem Repeat Sequences in Genome Organization}, AUTHOR = {Nikumbh, Sarvesh and Pfeifer, Nico}, LANGUAGE = {eng}, ISSN = {1471-2105}, DOI = {10.1186/s12859-017-1624-x}, PUBLISHER = {BioMed Central}, ADDRESS = {London}, YEAR = {2017}, MARGINALMARK = {$\bullet$}, JOURNAL = {BMC Bioinformatics}, VOLUME = {18}, PAGES = {1--16}, EID = {218}, }
Endnote
%0 Journal Article %A Nikumbh, Sarvesh %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 Genetic Sequence-based Prediction of Long-range Chromatin Interactions Suggests a Potential Role of Short Tandem Repeat Sequences in Genome Organization : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002D-26AD-4 %R 10.1186/s12859-017-1624-x %7 2017-04-18 %D 2017 %8 18.04.2017 %J BMC Bioinformatics %V 18 %& 1 %P 1 - 16 %Z sequence number: 218 %I BioMed Central %C London %@ false
16. Pironti A, Walter H, Pfeifer N, Knops E, Lübke N, Büch J, Di Giambenedetto S, Kaiser R, Lengauer T: Determination of Phenotypic Resistance Cutoffs from Routine Clinical Data. Journal of Acquired Immune Deficiency Syndromes 2017, 74.
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@article{Pironti_Pfeifer_Lengauer2017, TITLE = {Determination of Phenotypic Resistance Cutoffs from Routine Clinical Data}, AUTHOR = {Pironti, Alejandro and Walter, Hauke and Pfeifer, Nico and Knops, Elena and L{\"u}bke, Nadine and B{\"u}ch, Joachim and Di Giambenedetto, Simona and Kaiser, Rolf and Lengauer, Thomas}, LANGUAGE = {eng}, DOI = {10.1097/QAI.0000000000001198}, PUBLISHER = {Lippincott Williams \& Wilkins}, ADDRESS = {Philadelphia, PA}, YEAR = {2017}, MARGINALMARK = {$\bullet$}, JOURNAL = {Journal of Acquired Immune Deficiency Syndromes}, VOLUME = {74}, NUMBER = {5}, PAGES = {e129--e137}, }
Endnote
%0 Journal Article %A Pironti, Alejandro %A Walter, Hauke %A Pfeifer, Nico %A Knops, Elena %A Lübke, Nadine %A Büch, Joachim %A Di Giambenedetto, Simona %A Kaiser, Rolf %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 External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Determination of Phenotypic Resistance Cutoffs from Routine Clinical Data : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002C-3F1D-D %R 10.1097/QAI.0000000000001198 %7 2017 %D 2017 %J Journal of Acquired Immune Deficiency Syndromes %O JAIDS %V 74 %N 5 %& e129 %P e129 - e137 %I Lippincott Williams & Wilkins %C Philadelphia, PA
17. Pironti A, Pfeifer N, Walter H, Jensen B-EO, Zazzi M, Gomes P, Kaiser R, Lengauer T: Using Drug Exposure for Predicting Drug Resistance – A data-driven Genotypic Interpretation Tool. PLoS One 2017, 12.
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@article{Pironti_Pfeifer_Lengauer_2017, TITLE = {Using Drug Exposure for Predicting Drug Resistance -- A data-driven Genotypic Interpretation Tool}, AUTHOR = {Pironti, Alejandro and Pfeifer, Nico and Walter, Hauke and Jensen, Bj{\"o}rn-Erik O. and Zazzi, Maurizio and Gomes, Perp{\'e}tua and Kaiser, Rolf and Lengauer, Thomas}, LANGUAGE = {eng}, ISSN = {1932-6203}, DOI = {10.1371/journal.pone.0174992}, PUBLISHER = {Public Library of Science}, ADDRESS = {San Francisco, CA}, YEAR = {2017}, MARGINALMARK = {$\bullet$}, JOURNAL = {PLoS One}, VOLUME = {12}, NUMBER = {4}, EID = {e0174992}, }
Endnote
%0 Journal Article %A Pironti, Alejandro %A Pfeifer, Nico %A Walter, Hauke %A Jensen, Björn-Erik O. %A Zazzi, Maurizio %A Gomes, Perpétua %A Kaiser, Rolf %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 External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Using Drug Exposure for Predicting Drug Resistance – A data-driven Genotypic Interpretation Tool : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002D-48E5-0 %R 10.1371/journal.pone.0174992 %7 2017-04-10 %D 2017 %8 10.04.2017 %J PLoS One %V 12 %N 4 %Z sequence number: e0174992 %I Public Library of Science %C San Francisco, CA %@ false
18. Schmidt F, Gasparoni N, Gasparoni G, Gianmoena K, Cadenas C, Polansky JK, Ebert P, Nordström K, Barann M, Sinha A, Fröhler S, Xiong J, Dheghani Amirabad A, Behjati Ardakani F, Hutter B, Zipprich G, Felder B, Eils J, Brors B, Chen W, Hengstler JG, Hamann A, Lengauer T, Rosenstiel P, Walter J, Schulz MH: Combining Transcription Factor Binding Affinities with Open-Chromatin Data for Accurate Gene Expression Prediction. Nucleic Acids Research 2017, 45.
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@article{pmid27899623, TITLE = {Combining Transcription Factor Binding Affinities with Open-Chromatin Data for Accurate Gene Expression Prediction}, AUTHOR = {Schmidt, Florian and Gasparoni, Nina and Gasparoni, Gilles and Gianmoena, Kathrin and Cadenas, Cristina and Polansky, Julia K. and Ebert, Peter and Nordstr{\"o}m, Karl and Barann, Matthias and Sinha, Anupam and Fr{\"o}hler, Sebastian and Xiong, Jieyi and Dheghani Amirabad, Azim and Behjati Ardakani, Fatemeh and Hutter, Barbara and Zipprich, Gideon and Felder, B{\"a}rbel and Eils, J{\"u}rgen and Brors, Benedikt and Chen, Wei and Hengstler, Jan G. and Hamann, Alf and Lengauer, Thomas and Rosenstiel, Philip and Walter, J{\"o}rn and Schulz, Marcel H.}, LANGUAGE = {eng}, ISSN = {0305-1048}, DOI = {10.1093/nar/gkw1061}, PUBLISHER = {Oxford University Press}, ADDRESS = {Oxford}, YEAR = {2017}, MARGINALMARK = {$\bullet$}, DATE = {2017}, JOURNAL = {Nucleic Acids Research}, VOLUME = {45}, NUMBER = {1}, PAGES = {54--66}, }
Endnote
%0 Journal Article %A Schmidt, Florian %A Gasparoni, Nina %A Gasparoni, Gilles %A Gianmoena, Kathrin %A Cadenas, Cristina %A Polansky, Julia K. %A Ebert, Peter %A Nordström, Karl %A Barann, Matthias %A Sinha, Anupam %A Fröhler, Sebastian %A Xiong, Jieyi %A Dheghani Amirabad, Azim %A Behjati Ardakani, Fatemeh %A Hutter, Barbara %A Zipprich, Gideon %A Felder, Bärbel %A Eils, Jürgen %A Brors, Benedikt %A Chen, Wei %A Hengstler, Jan G. %A Hamann, Alf %A Lengauer, Thomas %A Rosenstiel, Philip %A Walter, Jörn %A Schulz, Marcel H. %+ 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 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 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 Combining Transcription Factor Binding Affinities with Open-Chromatin Data for Accurate Gene Expression Prediction : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002C-378F-F %R 10.1093/nar/gkw1061 %7 2016 %D 2017 %J Nucleic Acids Research %O Nucleic Acids Res %V 45 %N 1 %& 54 %P 54 - 66 %I Oxford University Press %C Oxford %@ false
19. Sheffield NC, Pierron G, Klughammer J, Datlinger P, Schönegger A, Schuster M, Hadler J, Surdez D, Guillemot D, Lapouble E, Freneaux P, Champigneulle J, Bouvier R, Walder D, Ambros IM, Hutter C, Sorz E, Amaral AT, de Álava E, Schallmoser K, Strunk D, Rinner B, Liegl-Atzwanger B, Huppertz B, Leithner A, de Pinieux G, Terrier P, Laurence V, Michon J, Ladenstein R, et al.: DNA Methylation Heterogeneity Defines a Disease Spectrum in Ewing Sarcoma. Nature Medicine 2017, 23.
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@article{Sheffield2017, TITLE = {{DNA} methylation heterogeneity defines a disease spectrum in {Ewing} sarcoma}, AUTHOR = {Sheffield, Nathan C. and Pierron, Gaelle and Klughammer, Johanna and Datlinger, Paul and Sch{\"o}negger, Andreas and Schuster, Michael and Hadler, Johanna and Surdez, Didier and Guillemot, Delphine and Lapouble, Eve and Freneaux, Paul and Champigneulle, Jacqueline and Bouvier, Raymonde and Walder, Diana and Ambros, Ingeborg M. and Hutter, Caroline and Sorz, Eva and Amaral, Ana T. and de {\'A}lava, Enrique and Schallmoser, Katharina and Strunk, Dirk and Rinner, Beate and Liegl-Atzwanger, Bernadette and Huppertz, Berthold and Leithner, Andreas and de Pinieux, Gonzague and Terrier, Philippe and Laurence, Val{\'e}rie and Michon, Jean and Ladenstein, Ruth and Holter, Wolfgang and Windhager, Reinhard and Dirksen, Uta and Ambros, Peter F. and Delattre, Olivier and Kovar, Heinrich and Bock, Christoph and Tomazou, Eleni M.}, LANGUAGE = {eng}, ISSN = {1078-8956}, DOI = {10.1038/nm.4273}, PUBLISHER = {Nature Publishing Group}, ADDRESS = {New York, NY}, YEAR = {2017}, MARGINALMARK = {$\bullet$}, DATE = {2017}, JOURNAL = {Nature Medicine}, VOLUME = {23}, NUMBER = {3}, PAGES = {386--395}, }
Endnote
%0 Journal Article %A Sheffield, Nathan C. %A Pierron, Gaelle %A Klughammer, Johanna %A Datlinger, Paul %A Schönegger, Andreas %A Schuster, Michael %A Hadler, Johanna %A Surdez, Didier %A Guillemot, Delphine %A Lapouble, Eve %A Freneaux, Paul %A Champigneulle, Jacqueline %A Bouvier, Raymonde %A Walder, Diana %A Ambros, Ingeborg M. %A Hutter, Caroline %A Sorz, Eva %A Amaral, Ana T. %A de Álava, Enrique %A Schallmoser, Katharina %A Strunk, Dirk %A Rinner, Beate %A Liegl-Atzwanger, Bernadette %A Huppertz, Berthold %A Leithner, Andreas %A de Pinieux, Gonzague %A Terrier, Philippe %A Laurence, Valérie %A Michon, Jean %A Ladenstein, Ruth %A Holter, Wolfgang %A Windhager, Reinhard %A Dirksen, Uta %A Ambros, Peter F. %A Delattre, Olivier %A Kovar, Heinrich %A Bock, Christoph %A Tomazou, Eleni M. %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations 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 %T DNA Methylation Heterogeneity Defines a Disease Spectrum in Ewing Sarcoma : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002C-CBE6-E %R 10.1038/nm.4273 %7 2017-01-30 %D 2017 %J Nature Medicine %O Nat. Med. %V 23 %N 3 %& 386 %P 386 - 395 %I Nature Publishing Group %C New York, NY %@ false
20. Towards Multiple Kernel Principal Component Analysis for Integrative Analysis of Tumor Samples [http://arxiv.org/abs/1701.00422]
(arXiv: 1701.00422)
Abstract
Personalized treatment of patients based on tissue-specific cancer subtypes has strongly increased the efficacy of the chosen therapies. Even though the amount of data measured for cancer patients has increased over the last years, most cancer subtypes are still diagnosed based on individual data sources (e.g. gene expression data). We propose an unsupervised data integration method based on kernel principal component analysis. Principal component analysis is one of the most widely used techniques in data analysis. Unfortunately, the straight-forward multiple-kernel extension of this method leads to the use of only one of the input matrices, which does not fit the goal of gaining information from all data sources. Therefore, we present a scoring function to determine the impact of each input matrix. The approach enables visualizing the integrated data and subsequent clustering for cancer subtype identification. Due to the nature of the method, no free parameters have to be set. We apply the methodology to five different cancer data sets and demonstrate its advantages in terms of results and usability.
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@online{SpeicherarXiv2017, TITLE = {Towards Multiple Kernel Principal Component Analysis for Integrative Analysis of Tumor Samples}, AUTHOR = {Speicher, Nora K. and Pfeifer, Nico}, LANGUAGE = {eng}, URL = {http://arxiv.org/abs/1701.00422}, EPRINT = {1701.00422}, EPRINTTYPE = {arXiv}, YEAR = {2017}, MARGINALMARK = {$\bullet$}, ABSTRACT = {Personalized treatment of patients based on tissue-specific cancer subtypes has strongly increased the efficacy of the chosen therapies. Even though the amount of data measured for cancer patients has increased over the last years, most cancer subtypes are still diagnosed based on individual data sources (e.g. gene expression data). We propose an unsupervised data integration method based on kernel principal component analysis. Principal component analysis is one of the most widely used techniques in data analysis. Unfortunately, the straight-forward multiple-kernel extension of this method leads to the use of only one of the input matrices, which does not fit the goal of gaining information from all data sources. Therefore, we present a scoring function to determine the impact of each input matrix. The approach enables visualizing the integrated data and subsequent clustering for cancer subtype identification. Due to the nature of the method, no free parameters have to be set. We apply the methodology to five different cancer data sets and demonstrate its advantages in terms of results and usability.}, }
Endnote
%0 Report %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 Towards Multiple Kernel Principal Component Analysis for Integrative Analysis of Tumor Samples : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002C-4D68-3 %U http://arxiv.org/abs/1701.00422 %D 2017 %X Personalized treatment of patients based on tissue-specific cancer subtypes has strongly increased the efficacy of the chosen therapies. Even though the amount of data measured for cancer patients has increased over the last years, most cancer subtypes are still diagnosed based on individual data sources (e.g. gene expression data). We propose an unsupervised data integration method based on kernel principal component analysis. Principal component analysis is one of the most widely used techniques in data analysis. Unfortunately, the straight-forward multiple-kernel extension of this method leads to the use of only one of the input matrices, which does not fit the goal of gaining information from all data sources. Therefore, we present a scoring function to determine the impact of each input matrix. The approach enables visualizing the integrated data and subsequent clustering for cancer subtype identification. Due to the nature of the method, no free parameters have to be set. We apply the methodology to five different cancer data sets and demonstrate its advantages in terms of results and usability. %K Statistics, Machine Learning, stat.ML