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1. Ahmad M, Helms V, Kalinina OV, Lengauer T: Relative Principal Components Analysis: Application to Analyzing Biomolecular Conformational Changes. Journal of Chemical Theory and Computation 2019, 15.
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@article{Ahmad2019, TITLE = {Relative Principal Components Analysis: {A}pplication to Analyzing Biomolecular Conformational Changes}, AUTHOR = {Ahmad, Mazen and Helms, Volkhard and Kalinina, Olga V. and Lengauer, Thomas}, LANGUAGE = {eng}, ISSN = {1549-9618}, DOI = {10.1021/acs.jctc.8b01074}, PUBLISHER = {ACM}, ADDRESS = {Washington, D.C.}, YEAR = {2019}, MARGINALMARK = {$\bullet$}, DATE = {2019}, JOURNAL = {Journal of Chemical Theory and Computation}, VOLUME = {15}, NUMBER = {4}, PAGES = {2166--2178}, }
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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 Relative Principal Components Analysis: Application to Analyzing Biomolecular Conformational Changes : %G eng %U http://hdl.handle.net/21.11116/0000-0003-8671-6 %R 10.1021/acs.jctc.8b01074 %7 2019 %D 2019 %J Journal of Chemical Theory and Computation %O J. Chem. Theory Comput. %V 15 %N 4 %& 2166 %P 2166 - 2178 %I ACM %C Washington, D.C. %@ false
2. Chaisson MJP, Sanders AD, Zhao X, Malhotra A, Porubsky D, Rausch T, Gardner EJ, Rodriguez OL, Guo L, Collins RL, Fan X, Wen J, Handsaker RE, Fairley S, Kronenberg ZN, Kong X, Hormozdiari F, Lee D, Wenger AM, Hastie AR, Antaki D, Anantharaman T, Audano PA, Brand H, Cantsilieris S, Cao H, Cerveira E, Chen C, Chen X, Chin C-S, et al.: Multi-platform Discovery of Haplotype-resolved Structural Variation in Human Genomes. Nature Communications 2019, 10.
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@article{Chaisson2019, TITLE = {Multi-platform Discovery of Haplotype-resolved Structural Variation in Human Genomes}, AUTHOR = {Chaisson, Mark J. P. and Sanders, Ashley D. and Zhao, Xuefang and Malhotra, Ankit and Porubsky, David and Rausch, Tobias and Gardner, Eugene J. and Rodriguez, Oscar L. and Guo, Li and Collins, Ryan L. and Fan, Xian and Wen, Jia and Handsaker, Robert E. and Fairley, Susan and Kronenberg, Zev N. and Kong, Xiangmeng and Hormozdiari, Fereydoun and Lee, Dillon and Wenger, Aaron M. and Hastie, Alex R. and Antaki, Danny and Anantharaman, Thomas and Audano, Peter A. and Brand, Harrison and Cantsilieris, Stuart and Cao, Han and Cerveira, Eliza and Chen, Chong and Chen, Xintong and Chin, Chen-Shan and Chong, Zechen and Chuang, Nelson T. and Lambert, Christine C. and Church, Deanna M. and Clarke, Laura and Farrell, Andrew and Flores, Joey and Galeev, Timur and Gorkin, David U. and Gujral, Madhusudan and Guryev, Victor and Heaton, William Haynes and Korlach, Jonas and Kumar, Sushant and Kwon, Jee Young and Lam, Ernest T. and Lee, Jong Eun and Lee, Joyce and Lee, Wan-Ping and Lee, Sau Peng and Li, Shantao and Marks, Patrick and Viaud-Martinez, Karine and Meiers, Sascha and Munson, Katherine M. and Navarro, Fabio C. P. and Nelson, Bradley J. and Nodzak, Conor and Noor, Amina and Kyriazopoulou-Panagiotopoulou, Sofia and Pang, Andy W. C. and Qiu, Yunjiang and Rosanio, Gabriel and Ryan, Mallory and Stuetz, Adrian and Spierings, Diana C. J. and Ward, Alistair and Welch, AnneMarie E. and Xiao, Ming and Xu, Wei and Zhang, Chengsheng and Zhu, Qihui and Zheng-Bradley, Xiangqun and Lowy, Ernesto and Yakneen, Sergei and McCarroll, Steven and Jun, Goo and Ding, Li and Koh, Chong Lek and Ren, Bing and Flicek, Paul and Chen, Ken and Gerstein, Mark B. and Kwok, Pui-Yan and Lansdorp, Peter M. and Marth, Gabor T. and Sebat, Jonathan and Shi, Xinghua and Bashir, Ali and Ye, Kai and Devine, Scott E. and Talkowski, Michael E. and Mills, Ryan E. and Marschall, Tobias and Korbel, Jan O. and Eichler, Evan E. and Lee, Charles}, LANGUAGE = {eng}, ISSN = {2041-1723}, DOI = {10.1038/s41467-018-08148-z}, PUBLISHER = {Nature Publishing Group}, ADDRESS = {London}, YEAR = {2019}, MARGINALMARK = {$\bullet$}, JOURNAL = {Nature Communications}, VOLUME = {10}, EID = {1784}, }
Endnote
%0 Journal Article %A Chaisson, Mark J. P. %A Sanders, Ashley D. %A Zhao, Xuefang %A Malhotra, Ankit %A Porubsky, David %A Rausch, Tobias %A Gardner, Eugene J. %A Rodriguez, Oscar L. %A Guo, Li %A Collins, Ryan L. %A Fan, Xian %A Wen, Jia %A Handsaker, Robert E. %A Fairley, Susan %A Kronenberg, Zev N. %A Kong, Xiangmeng %A Hormozdiari, Fereydoun %A Lee, Dillon %A Wenger, Aaron M. %A Hastie, Alex R. %A Antaki, Danny %A Anantharaman, Thomas %A Audano, Peter A. %A Brand, Harrison %A Cantsilieris, Stuart %A Cao, Han %A Cerveira, Eliza %A Chen, Chong %A Chen, Xintong %A Chin, Chen-Shan %A Chong, Zechen %A Chuang, Nelson T. %A Lambert, Christine C. %A Church, Deanna M. %A Clarke, Laura %A Farrell, Andrew %A Flores, Joey %A Galeev, Timur %A Gorkin, David U. %A Gujral, Madhusudan %A Guryev, Victor %A Heaton, William Haynes %A Korlach, Jonas %A Kumar, Sushant %A Kwon, Jee Young %A Lam, Ernest T. %A Lee, Jong Eun %A Lee, Joyce %A Lee, Wan-Ping %A Lee, Sau Peng %A Li, Shantao %A Marks, Patrick %A Viaud-Martinez, Karine %A Meiers, Sascha %A Munson, Katherine M. %A Navarro, Fabio C. P. %A Nelson, Bradley J. %A Nodzak, Conor %A Noor, Amina %A Kyriazopoulou-Panagiotopoulou, Sofia %A Pang, Andy W. C. %A Qiu, Yunjiang %A Rosanio, Gabriel %A Ryan, Mallory %A Stuetz, Adrian %A Spierings, Diana C. J. %A Ward, Alistair %A Welch, AnneMarie E. %A Xiao, Ming %A Xu, Wei %A Zhang, Chengsheng %A Zhu, Qihui %A Zheng-Bradley, Xiangqun %A Lowy, Ernesto %A Yakneen, Sergei %A McCarroll, Steven %A Jun, Goo %A Ding, Li %A Koh, Chong Lek %A Ren, Bing %A Flicek, Paul %A Chen, Ken %A Gerstein, Mark B. %A Kwok, Pui-Yan %A Lansdorp, Peter M. %A Marth, Gabor T. %A Sebat, Jonathan %A Shi, Xinghua %A Bashir, Ali %A Ye, Kai %A Devine, Scott E. %A Talkowski, Michael E. %A Mills, Ryan E. %A Marschall, Tobias %A Korbel, Jan O. %A Eichler, Evan E. %A Lee, Charles %+ External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations 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 Multi-platform Discovery of Haplotype-resolved Structural Variation in Human Genomes : %G eng %U http://hdl.handle.net/21.11116/0000-0003-865E-D %R 10.1038/s41467-018-08148-z %7 2019 %D 2019 %J Nature Communications %O Nat. Commun. %V 10 %Z sequence number: 1784 %I Nature Publishing Group %C London %@ false
3. Durai DA, Schulz MH: Improving in-silico Normalization using Read Weights. Scientific Reports 2019, 9.
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@article{Durai2019, TITLE = {Improving in-silico Normalization using Read Weights}, AUTHOR = {Durai, Dilip Ariyur and Schulz, Marcel Holger}, LANGUAGE = {eng}, ISSN = {2045-2322}, DOI = {10.1038/s41598-019-41502-9}, PUBLISHER = {Nature Publishing Group}, ADDRESS = {London, UK}, YEAR = {2019}, MARGINALMARK = {$\bullet$}, JOURNAL = {Scientific Reports}, VOLUME = {9}, EID = {5133}, }
Endnote
%0 Journal Article %A Durai, Dilip Ariyur %A Schulz, Marcel Holger %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T Improving in-silico Normalization using Read Weights : %G eng %U http://hdl.handle.net/21.11116/0000-0003-5F5F-A %R 10.1038/s41598-019-41502-9 %7 2019 %D 2019 %J Scientific Reports %O Sci. Rep. %V 9 %Z sequence number: 5133 %I Nature Publishing Group %C London, UK %@ false %U https://doi.org/10.1038/s41598-019-41502-9
4. Ebert P: What we leave behind : reproducibility in chromatin analysis within and across species. Universität des Saarlandes; 2019.
Abstract
Epigenetics is the field of biology that investigates heritable factors regulating gene expression without being directly encoded in the genome of an organism. The human genome is densely packed inside a cell's nucleus in the form of chromatin. Certain constituents of chromatin play a vital role as epigenetic factors in the dynamic regulation of gene expression. Epigenetic changes on the chromatin level are thus an integral part of the mechanisms governing the development of the functionally diverse cell types in multicellular species such as human. Studying these mechanisms is not only important to understand the biology of healthy cells, but also necessary to comprehend the epigenetic component in the formation of many complex diseases. Modern wet lab technology enables scientists to probe the epigenome with high throughput and in extensive detail. The fast generation of epigenetic datasets burdens computational researchers with the challenge of rapidly performing elaborate analyses without compromising on the scientific reproducibility of the reported findings. To facilitate reproducible computational research in epigenomics, this thesis proposes a task-oriented metadata model, relying on web technology and supported by database engineering, that aims at consistent and human-readable documentation of standardized computational workflows. The suggested approach features, e.g., computational validation of metadata records, automatic error detection, and progress monitoring of multi-step analyses, and was successfully field-tested as part of a large epigenome research consortium. This work leaves aside theoretical considerations, and intentionally emphasizes the realistic need of providing scientists with tools that assist them in performing reproducible research. Irrespective of the technological progress, the dynamic and cell-type specific nature of the epigenome commonly requires restricting the number of analyzed samples due to resource limitations. The second project of this thesis introduces the software tool SCIDDO, which has been developed for the differential chromatin analysis of cellular samples with potentially limited availability. By combining statistics, algorithmics, and best practices for robust software development, SCIDDO can quickly identify biologically meaningful regions of differential chromatin marking between cell types. We demonstrate SCIDDO's usefulness in an exemplary study in which we identify regions that establish a link between chromatin and gene expression changes. SCIDDO's quantitative approach to differential chromatin analysis is user-customizable, providing the necessary flexibility to adapt SCIDDO to specific research tasks. Given the functional diversity of cell types and the dynamics of the epigenome in response to environmental changes, it is hardly realistic to map the complete epigenome even for a single organism like human or mouse. For non-model organisms, e.g., cow, pig, or dog, epigenome data is particularly scarce. The third project of this thesis investigates to what extent bioinformatics methods can compensate for the comparatively little effort that is invested in charting the epigenome of non-model species. This study implements a large integrative analysis pipeline, including state-of-the-art machine learning, to transfer chromatin data for predictive modeling between 13 species. The evidence presented here indicates that a partial regulatory epigenetic signal is stably retained even over millions of years of evolutionary distance between the considered species. This finding suggests complementary and cost-effective ways for bioinformatics to contribute to comparative epigenome analysis across species boundaries.
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@phdthesis{Ebertphd2019, TITLE = {What we leave behind : reproducibility in chromatin analysis within and across species}, AUTHOR = {Ebert, Peter}, LANGUAGE = {eng}, URL = {urn:nbn:de:bsz:291--ds-278311}, DOI = {doi.org/10.22028/D291-27831}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2019}, MARGINALMARK = {$\bullet$}, DATE = {2019}, ABSTRACT = {Epigenetics is the field of biology that investigates heritable factors regulating gene expression without being directly encoded in the genome of an organism. The human genome is densely packed inside a cell's nucleus in the form of chromatin. Certain constituents of chromatin play a vital role as epigenetic factors in the dynamic regulation of gene expression. Epigenetic changes on the chromatin level are thus an integral part of the mechanisms governing the development of the functionally diverse cell types in multicellular species such as human. Studying these mechanisms is not only important to understand the biology of healthy cells, but also necessary to comprehend the epigenetic component in the formation of many complex diseases. Modern wet lab technology enables scientists to probe the epigenome with high throughput and in extensive detail. The fast generation of epigenetic datasets burdens computational researchers with the challenge of rapidly performing elaborate analyses without compromising on the scientific reproducibility of the reported findings. To facilitate reproducible computational research in epigenomics, this thesis proposes a task-oriented metadata model, relying on web technology and supported by database engineering, that aims at consistent and human-readable documentation of standardized computational workflows. The suggested approach features, e.g., computational validation of metadata records, automatic error detection, and progress monitoring of multi-step analyses, and was successfully field-tested as part of a large epigenome research consortium. This work leaves aside theoretical considerations, and intentionally emphasizes the realistic need of providing scientists with tools that assist them in performing reproducible research. Irrespective of the technological progress, the dynamic and cell-type specific nature of the epigenome commonly requires restricting the number of analyzed samples due to resource limitations. The second project of this thesis introduces the software tool SCIDDO, which has been developed for the differential chromatin analysis of cellular samples with potentially limited availability. By combining statistics, algorithmics, and best practices for robust software development, SCIDDO can quickly identify biologically meaningful regions of differential chromatin marking between cell types. We demonstrate SCIDDO's usefulness in an exemplary study in which we identify regions that establish a link between chromatin and gene expression changes. SCIDDO's quantitative approach to differential chromatin analysis is user-customizable, providing the necessary flexibility to adapt SCIDDO to specific research tasks. Given the functional diversity of cell types and the dynamics of the epigenome in response to environmental changes, it is hardly realistic to map the complete epigenome even for a single organism like human or mouse. For non-model organisms, e.g., cow, pig, or dog, epigenome data is particularly scarce. The third project of this thesis investigates to what extent bioinformatics methods can compensate for the comparatively little effort that is invested in charting the epigenome of non-model species. This study implements a large integrative analysis pipeline, including state-of-the-art machine learning, to transfer chromatin data for predictive modeling between 13 species. The evidence presented here indicates that a partial regulatory epigenetic signal is stably retained even over millions of years of evolutionary distance between the considered species. This finding suggests complementary and cost-effective ways for bioinformatics to contribute to comparative epigenome analysis across species boundaries.}, }
Endnote
%0 Thesis %A Ebert, Peter %Y Lengauer, Thomas %A referee: Lenhof, Hans-Peter %A referee: Weikum, Gerhard %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society International Max Planck Research School, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Algorithms and Complexity, MPI for Informatics, Max Planck Society Databases and Information Systems, MPI for Informatics, Max Planck Society %T What we leave behind : reproducibility in chromatin analysis within and across species : %G eng %U http://hdl.handle.net/21.11116/0000-0003-9ADF-5 %R doi.org/10.22028/D291-27831 %U urn:nbn:de:bsz:291--ds-278311 %I Universität des Saarlandes %C Saarbrücken %D 2019 %P 152 p. %V phd %9 phd %X Epigenetics is the field of biology that investigates heritable factors regulating gene expression without being directly encoded in the genome of an organism. The human genome is densely packed inside a cell's nucleus in the form of chromatin. Certain constituents of chromatin play a vital role as epigenetic factors in the dynamic regulation of gene expression. Epigenetic changes on the chromatin level are thus an integral part of the mechanisms governing the development of the functionally diverse cell types in multicellular species such as human. Studying these mechanisms is not only important to understand the biology of healthy cells, but also necessary to comprehend the epigenetic component in the formation of many complex diseases. Modern wet lab technology enables scientists to probe the epigenome with high throughput and in extensive detail. The fast generation of epigenetic datasets burdens computational researchers with the challenge of rapidly performing elaborate analyses without compromising on the scientific reproducibility of the reported findings. To facilitate reproducible computational research in epigenomics, this thesis proposes a task-oriented metadata model, relying on web technology and supported by database engineering, that aims at consistent and human-readable documentation of standardized computational workflows. The suggested approach features, e.g., computational validation of metadata records, automatic error detection, and progress monitoring of multi-step analyses, and was successfully field-tested as part of a large epigenome research consortium. This work leaves aside theoretical considerations, and intentionally emphasizes the realistic need of providing scientists with tools that assist them in performing reproducible research. Irrespective of the technological progress, the dynamic and cell-type specific nature of the epigenome commonly requires restricting the number of analyzed samples due to resource limitations. The second project of this thesis introduces the software tool SCIDDO, which has been developed for the differential chromatin analysis of cellular samples with potentially limited availability. By combining statistics, algorithmics, and best practices for robust software development, SCIDDO can quickly identify biologically meaningful regions of differential chromatin marking between cell types. We demonstrate SCIDDO's usefulness in an exemplary study in which we identify regions that establish a link between chromatin and gene expression changes. SCIDDO's quantitative approach to differential chromatin analysis is user-customizable, providing the necessary flexibility to adapt SCIDDO to specific research tasks. Given the functional diversity of cell types and the dynamics of the epigenome in response to environmental changes, it is hardly realistic to map the complete epigenome even for a single organism like human or mouse. For non-model organisms, e.g., cow, pig, or dog, epigenome data is particularly scarce. The third project of this thesis investigates to what extent bioinformatics methods can compensate for the comparatively little effort that is invested in charting the epigenome of non-model species. This study implements a large integrative analysis pipeline, including state-of-the-art machine learning, to transfer chromatin data for predictive modeling between 13 species. The evidence presented here indicates that a partial regulatory epigenetic signal is stably retained even over millions of years of evolutionary distance between the considered species. This finding suggests complementary and cost-effective ways for bioinformatics to contribute to comparative epigenome analysis across species boundaries. %U https://publikationen.sulb.uni-saarland.de/handle/20.500.11880/27387
5. Gérard D, Schmidt F, Ginolhac A, Schmitz M, Halder R, Ebert P, Schulz MH, Sauter T, Sinkkonen L: Temporal Enhancer Profiling of Parallel Lineages Identifies AHR and GLIS1 as Regulators of Mesenchymal Multipotency. Nucleic Acids Research 2019, 47.
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@article{Gerard2019, TITLE = {Temporal enhancer profiling of parallel lineages identifies {AHR} and {GLIS1} as regulators of mesenchymal multipotency}, AUTHOR = {G{\'e}rard, Deborah and Schmidt, Florian and Ginolhac, Aur{\'e}lien and Schmitz, Martine and Halder, Rashi and Ebert, Peter and Schulz, Marcel Holger and Sauter, Thomas and Sinkkonen, Lasse}, LANGUAGE = {eng}, ISSN = {0305-1048}, DOI = {10.1093/nar/gky1240}, PUBLISHER = {Oxford University Press}, ADDRESS = {Oxford}, YEAR = {2019}, MARGINALMARK = {$\bullet$}, DATE = {2019}, JOURNAL = {Nucleic Acids Research}, VOLUME = {47}, NUMBER = {3}, PAGES = {1141--1163}, }
Endnote
%0 Journal Article %A Gérard, Deborah %A Schmidt, Florian %A Ginolhac, Aurélien %A Schmitz, Martine %A Halder, Rashi %A Ebert, Peter %A Schulz, Marcel Holger %A Sauter, Thomas %A Sinkkonen, Lasse %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations %T Temporal Enhancer Profiling of Parallel Lineages Identifies AHR and GLIS1 as Regulators of Mesenchymal Multipotency : %G eng %U http://hdl.handle.net/21.11116/0000-0003-1AFD-4 %R 10.1093/nar/gky1240 %7 2018 %D 2019 %J Nucleic Acids Research %O Nucleic Acids Res %V 47 %N 3 %& 1141 %P 1141 - 1163 %I Oxford University Press %C Oxford %@ false
6. Karunanithi S, Simon M, Schulz MH: Automated Analysis of Small RNA Datasets with RAPID. PeerJ 2019, 7.
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@article{Karunanithi2019, TITLE = {Automated analysis of small {RNA} datasets with {RAPID}}, AUTHOR = {Karunanithi, Sivarajan and Simon, Martin and Schulz, Marcel Holger}, LANGUAGE = {eng}, ISSN = {2167-8359}, DOI = {10.7717/peerj.6710}, PUBLISHER = {PeerJ Inc.}, ADDRESS = {San Francisco, USA}, YEAR = {2019}, MARGINALMARK = {$\bullet$}, JOURNAL = {PeerJ}, VOLUME = {7}, EID = {e6710}, }
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%0 Journal Article %A Karunanithi, Sivarajan %A Simon, Martin %A Schulz, Marcel Holger %+ 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 Automated Analysis of Small RNA Datasets with RAPID : %G eng %U http://hdl.handle.net/21.11116/0000-0003-7D5F-8 %R 10.7717/peerj.6710 %7 2019 %D 2019 %J PeerJ %O PeerJ %V 7 %Z sequence number: e6710 %I PeerJ Inc. %C San Francisco, USA %@ false
7. Kosack L, Wingelhofer B, Popa A, Orlova A, Agerer B, Vilagos B, Majek P, Parapatics K, Lercher A, Ringler A, Klughammer J, Smyth M, Khamina K, Baazim H, de Araujo ED, Rosa DA, Park J, Tin G, Ahmar S, Gunning PT, Bock C, Siddle HV, Woods GM, Kubicek S, Murchison EP, Bennett KL, Moriggl R, Bergthaler A: The ERBB-STAT3 Axis Drives Tasmanian Devil Facial Tumor Disease. Cancer Cell 2019, 35.
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@article{Kosack2019, TITLE = {The {ERBB}-{STAT3} Axis Drives {T}asmanian Devil Facial Tumor Disease}, AUTHOR = {Kosack, Lindsay and Wingelhofer, Bettina and Popa, Alexandra and Orlova, Anna and Agerer, Benedikt and Vilagos, Bojan and Majek, Peter and Parapatics, Katja and Lercher, Alexander and Ringler, Anna and Klughammer, Johanna and Smyth, Mark and Khamina, Kseniya and Baazim, Hatoon and de Araujo, Elvin D. and Rosa, David A. and Park, Jisung and Tin, Gary and Ahmar, Siawash and Gunning, Patrick T. and Bock, Christoph and Siddle, Hannah V. and Woods, Gregory M. and Kubicek, Stefan and Murchison, Elizabeth P. and Bennett, Keiryn L. and Moriggl, Richard and Bergthaler, Andreas}, LANGUAGE = {eng}, ISSN = {1535-6108}, DOI = {10.1016/j.ccell.2018.11.018}, PUBLISHER = {Cell Press}, ADDRESS = {Cambridge, Mass.}, YEAR = {2019}, MARGINALMARK = {$\bullet$}, JOURNAL = {Cancer Cell}, VOLUME = {35}, NUMBER = {1}, PAGES = {125--139}, EID = {e9}, }
Endnote
%0 Journal Article %A Kosack, Lindsay %A Wingelhofer, Bettina %A Popa, Alexandra %A Orlova, Anna %A Agerer, Benedikt %A Vilagos, Bojan %A Majek, Peter %A Parapatics, Katja %A Lercher, Alexander %A Ringler, Anna %A Klughammer, Johanna %A Smyth, Mark %A Khamina, Kseniya %A Baazim, Hatoon %A de Araujo, Elvin D. %A Rosa, David A. %A Park, Jisung %A Tin, Gary %A Ahmar, Siawash %A Gunning, Patrick T. %A Bock, Christoph %A Siddle, Hannah V. %A Woods, Gregory M. %A Kubicek, Stefan %A Murchison, Elizabeth P. %A Bennett, Keiryn L. %A Moriggl, Richard %A Bergthaler, Andreas %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations 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 The ERBB-STAT3 Axis Drives Tasmanian Devil Facial Tumor Disease : %G eng %U http://hdl.handle.net/21.11116/0000-0002-F715-0 %R 10.1016/j.ccell.2018.11.018 %7 2019 %D 2019 %J Cancer Cell %O Cancer Cell %V 35 %N 1 %& 125 %P 125 - 139 %Z sequence number: e9 %I Cell Press %C Cambridge, Mass. %@ false
8. Li Z, Schulz MH, Look T, Begemann M, Zenke M, Costa IG: Identification of Transcription Factor Binding Sites using ATAC-seq. Genome Research 2019, 20.
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@article{Li2019, TITLE = {Identification of transcription factor binding sites using {ATAC}-seq}, AUTHOR = {Li, Zhijian and Schulz, Marcel Holger and Look, Thomas and Begemann, Matthias and Zenke, Martin and Costa, Ivan G.}, LANGUAGE = {eng}, ISSN = {1088-9051}, DOI = {10.1186/s13059-019-1642-2}, PUBLISHER = {Cold Spring Harbor Laboratory Press}, ADDRESS = {Cold Spring Harbor, N.Y.}, YEAR = {2019}, MARGINALMARK = {$\bullet$}, JOURNAL = {Genome Research}, VOLUME = {20}, EID = {45}, }
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%0 Journal Article %A Li, Zhijian %A Schulz, Marcel Holger %A Look, Thomas %A Begemann, Matthias %A Zenke, Martin %A Costa, Ivan G. %+ External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations %T Identification of Transcription Factor Binding Sites using ATAC-seq : %G eng %U http://hdl.handle.net/21.11116/0000-0003-2AF1-E %R 10.1186/s13059-019-1642-2 %7 2019 %D 2019 %J Genome Research %V 20 %Z sequence number: 45 %I Cold Spring Harbor Laboratory Press %C Cold Spring Harbor, N.Y. %@ false
9. Müller F, Scherer M, Assenov Y, Lutsik P, Walter J, Lengauer T, Bock C: RnBeads 2.0: Comprehensive Analysis of DNA Methylation Data. Genome Biology 2019, 20.
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@article{Mueller_GenomeBiology2019, TITLE = {{RnBeads} 2.0: {C}omprehensive analysis of {DNA} methylation data}, AUTHOR = {M{\"u}ller, Fabian and Scherer, Michael and Assenov, Yassen and Lutsik, Pavlo and Walter, J{\"o}rn and Lengauer, Thomas and Bock, Christoph}, LANGUAGE = {eng}, ISSN = {1465-6906}, DOI = {10.1186/s13059-019-1664-9}, PUBLISHER = {BioMed Central Ltd.}, ADDRESS = {London}, YEAR = {2019}, MARGINALMARK = {$\bullet$}, JOURNAL = {Genome Biology}, VOLUME = {20}, EID = {55}, }
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%0 Journal Article %A Müller, Fabian %A Scherer, Michael %A Assenov, Yassen %A Lutsik, Pavlo %A Walter, Jörn %A Lengauer, Thomas %A Bock, Christoph %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society 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 RnBeads 2.0: Comprehensive Analysis of DNA Methylation Data : %G eng %U http://hdl.handle.net/21.11116/0000-0003-2DF3-9 %R 10.1186/s13059-019-1664-9 %7 2019 %D 2019 %J Genome Biology %V 20 %Z sequence number: 55 %I BioMed Central Ltd. %C London %@ false
10. Neininger K, Marschall T, Helms V: SNP and Indel Frequencies at Transcription Start Sites and at Canonical and Alternative Translation Initiation Sites in the Human Genome. PLoS One 2019, 14.
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@article{Neininger2019, TITLE = {{SNP} and indel frequencies at transcription start sites and at canonical and alternative translation initiation sites in the human genome}, AUTHOR = {Neininger, Kerstin and Marschall, Tobias and Helms, Volkhard}, LANGUAGE = {eng}, ISSN = {1932-6203}, DOI = {10.1371/journal.pone.0214816}, PUBLISHER = {Public Library of Science}, ADDRESS = {San Francisco, CA}, YEAR = {2019}, MARGINALMARK = {$\bullet$}, JOURNAL = {PLoS One}, VOLUME = {14}, NUMBER = {4}, EID = {e0214816}, }
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%0 Journal Article %A Neininger, Kerstin %A Marschall, Tobias %A Helms, Volkhard %+ External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations %T SNP and Indel Frequencies at Transcription Start Sites and at Canonical and Alternative Translation Initiation Sites in the Human Genome : %G eng %U http://hdl.handle.net/21.11116/0000-0003-866B-E %R 10.1371/journal.pone.0214816 %7 2019-04-12 %D 2019 %8 12.04.2019 %J PLoS One %V 14 %N 4 %Z sequence number: e0214816 %I Public Library of Science %C San Francisco, CA %@ false
11. Pfitzer L, Moser C, Gegenfurtner F, Arner A, Foerster F, Atzberger C, Zisis T, Kubisch-Dohmen R, Busse J, Smith R, Timinszky G, Kalinina OV, Müller R, Wagner E, Vollmar AM, Zahler S: Targeting Actin Inhibits Repair of Doxorubicin-induced DNA Damage: A Novel Therapeutic Approach for Combination Therapy. Cell Death and Disease 2019, 10.
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@article{Pfitzer2019, TITLE = {Targeting actin inhibits repair of doxorubicin-induced {DNA} damage: {A} novel therapeutic approach for combination therapy}, AUTHOR = {Pfitzer, Lisa and Moser, Christina and Gegenfurtner, Florian and Arner, Anja and Foerster, Florian and Atzberger, Carina and Zisis, Themistoklis and Kubisch-Dohmen, Rebekka and Busse, Johanna and Smith, Rebecca and Timinszky, Gyula and Kalinina, Olga V. and M{\"u}ller, Rolf and Wagner, Ernst and Vollmar, Angelika M. and Zahler, Stefan}, LANGUAGE = {eng}, DOI = {10.1038/s41419-019-1546-9}, PUBLISHER = {Nature Publishing Group}, ADDRESS = {London}, YEAR = {2019}, MARGINALMARK = {$\bullet$}, JOURNAL = {Cell Death and Disease}, VOLUME = {10}, EID = {302}, }
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%0 Journal Article %A Pfitzer, Lisa %A Moser, Christina %A Gegenfurtner, Florian %A Arner, Anja %A Foerster, Florian %A Atzberger, Carina %A Zisis, Themistoklis %A Kubisch-Dohmen, Rebekka %A Busse, Johanna %A Smith, Rebecca %A Timinszky, Gyula %A Kalinina, Olga V. %A Müller, Rolf %A Wagner, Ernst %A Vollmar, Angelika M. %A Zahler, Stefan %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations %T Targeting Actin Inhibits Repair of Doxorubicin-induced DNA Damage: A Novel Therapeutic Approach for Combination Therapy : %G eng %U http://hdl.handle.net/21.11116/0000-0003-8A7E-5 %R 10.1038/s41419-019-1546-9 %7 2019 %D 2019 %J Cell Death and Disease %O Cell Death Dis %V 10 %Z sequence number: 302 %I Nature Publishing Group %C London
12. Schmidl C, Vladimer GI, Rendeiro AF, Schnabl S, Krausgruber T, Taubert C, Krall N, Pemovska T, Araghi M, Snijder B, Hubmann R, Ringler A, Runggatscher K, Demirtas D, Lopez de la Fuente O, Hilgarth M, Skrabs C, Porpaczy E, Gruber M, Hoermann G, Kubicek S, Staber PB, Shehata M, Superti-Furga G, Jaeger U, Bock C: Combined Chemosensitivity and Chromatin Profiling Prioritizes Drug Combinations in CLL. Nature Chemical Biology 2019, 15.
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@article{Schmidl2019, TITLE = {Combined Chemosensitivity and Chromatin Profiling Prioritizes Drug Combinations in {CLL}}, AUTHOR = {Schmidl, Christian and Vladimer, Gregory I. and Rendeiro, Andre F. and Schnabl, Susanne and Krausgruber, Thomas and Taubert, Christina and Krall, Nikolaus and Pemovska, Tea and Araghi, Mohammad and Snijder, Berend and Hubmann, Rainer and Ringler, Anna and Runggatscher, Kathrin and Demirtas, Dita and Lopez de la Fuente, Oscar and Hilgarth, Martin and Skrabs, Cathrin and Porpaczy, Edit and Gruber, Michaela and Hoermann, Gregor and Kubicek, Stefan and Staber, Philipp B. and Shehata, Medhat and Superti-Furga, Giulio and Jaeger, Ulrich and Bock, Christoph}, LANGUAGE = {eng}, ISSN = {1552-4450}, DOI = {10.1038/s41589-018-0205-2}, PUBLISHER = {Nature Pub. Group}, ADDRESS = {New York, NY}, YEAR = {2019}, MARGINALMARK = {$\bullet$}, DATE = {2019}, JOURNAL = {Nature Chemical Biology}, VOLUME = {15}, NUMBER = {3}, PAGES = {232--240}, }
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%0 Journal Article %A Schmidl, Christian %A Vladimer, Gregory I. %A Rendeiro, Andre F. %A Schnabl, Susanne %A Krausgruber, Thomas %A Taubert, Christina %A Krall, Nikolaus %A Pemovska, Tea %A Araghi, Mohammad %A Snijder, Berend %A Hubmann, Rainer %A Ringler, Anna %A Runggatscher, Kathrin %A Demirtas, Dita %A Lopez de la Fuente, Oscar %A Hilgarth, Martin %A Skrabs, Cathrin %A Porpaczy, Edit %A Gruber, Michaela %A Hoermann, Gregor %A Kubicek, Stefan %A Staber, Philipp B. %A Shehata, Medhat %A Superti-Furga, Giulio %A Jaeger, Ulrich %A Bock, Christoph %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations 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 %T Combined Chemosensitivity and Chromatin Profiling Prioritizes Drug Combinations in CLL : %G eng %U http://hdl.handle.net/21.11116/0000-0003-1434-C %R 10.1038/s41589-018-0205-2 %7 2019 %D 2019 %J Nature Chemical Biology %O Nat. Chem. Biol. %V 15 %N 3 %& 232 %P 232 - 240 %I Nature Pub. Group %C New York, NY %@ false
13. Schmidt F, Schulz MH: On the Problem of Confounders in Modeling Gene Expression. Bioinformatics 2019, 35.
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@article{Schmidt2019, TITLE = {On the Problem of Confounders in Modeling Gene Expression}, AUTHOR = {Schmidt, Florian and Schulz, Marcel Holger}, LANGUAGE = {eng}, ISSN = {1367-4803}, DOI = {10.1093/bioinformatics/bty674}, PUBLISHER = {Oxford University Press}, ADDRESS = {Oxford}, YEAR = {2019}, MARGINALMARK = {$\bullet$}, DATE = {2019}, JOURNAL = {Bioinformatics}, VOLUME = {35}, NUMBER = {4}, PAGES = {711--719}, }
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%0 Journal Article %A Schmidt, Florian %A Schulz, Marcel Holger %+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society %T On the Problem of Confounders in Modeling Gene Expression : %G eng %U http://hdl.handle.net/21.11116/0000-0003-2094-1 %R 10.1093/bioinformatics/bty674 %7 2018 %D 2019 %J Bioinformatics %V 35 %N 4 %& 711 %P 711 - 719 %I Oxford University Press %C Oxford %@ false
14. Yi G, Wierenga ATJ, Petraglia F, Narang P, Janssen-Megens EM, Mandoli A, Merkel A, Berentsen K, Kim B, Matarese F, Singh AA, Habibi E, Prange KHM, Mulder AB, Jansen JH, Clarke L, Heath S, van der Reijden BA, Flicek P, Yaspo M-L, Gut I, Bock C, Schuringa JJ, Altucci L, Vellenga E, Stunnenberg HG, Martens J, H. A: Chromatin-Based Classification of Genetically Heterogeneous AMLs into Two Distinct Subtypes with Diverse Stemness Phenotypes. Cell Reports 2019, 26.
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@article{Yi2019, TITLE = {Chromatin-Based Classification of Genetically Heterogeneous {AMLs} into Two Distinct Subtypes with Diverse Stemness Phenotypes}, AUTHOR = {Yi, Guoqiang and Wierenga, Albertus T. J. and Petraglia, Francesca and Narang, Pankaj and Janssen-Megens, Eva M. and Mandoli, Amit and Merkel, Angelika and Berentsen, Kim and Kim, Bowon and Matarese, Filomena and Singh, Abhishek A. and Habibi, Ehsan and Prange, Koen H. M. and Mulder, Andre B. and Jansen, Joop H. and Clarke, Laura and Heath, Simon and van der Reijden, Bert A. and Flicek, Paul and Yaspo, Marie-Laure and Gut, Ivo and Bock, Christoph and Schuringa, Jan Jacob and Altucci, Lucia and Vellenga, Edo and Stunnenberg, Hendrik G. and Martens, Joost and H., A.}, LANGUAGE = {eng}, ISSN = {2211-1247}, DOI = {10.1016/j.celrep.2018.12.098}, PUBLISHER = {Cell Press}, ADDRESS = {Maryland Heights, MO}, YEAR = {2019}, MARGINALMARK = {$\bullet$}, JOURNAL = {Cell Reports}, VOLUME = {26}, NUMBER = {4}, PAGES = {1059--1069}, EID = {e6}, }
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%0 Journal Article %A Yi, Guoqiang %A Wierenga, Albertus T. J. %A Petraglia, Francesca %A Narang, Pankaj %A Janssen-Megens, Eva M. %A Mandoli, Amit %A Merkel, Angelika %A Berentsen, Kim %A Kim, Bowon %A Matarese, Filomena %A Singh, Abhishek A. %A Habibi, Ehsan %A Prange, Koen H. M. %A Mulder, Andre B. %A Jansen, Joop H. %A Clarke, Laura %A Heath, Simon %A van der Reijden, Bert A. %A Flicek, Paul %A Yaspo, Marie-Laure %A Gut, Ivo %A Bock, Christoph %A Schuringa, Jan Jacob %A Altucci, Lucia %A Vellenga, Edo %A Stunnenberg, Hendrik G. %A Martens, Joost %A H., A. %+ External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society External Organizations External Organizations External Organizations External Organizations External Organizations External Organizations %T Chromatin-Based Classification of Genetically Heterogeneous AMLs into Two Distinct Subtypes with Diverse Stemness Phenotypes : %G eng %U http://hdl.handle.net/21.11116/0000-0002-F6CB-4 %R 10.1016/j.celrep.2018.12.098 %7 2019 %D 2019 %J Cell Reports %V 26 %N 4 %& 1059 %P 1059 - 1069 %Z sequence number: e6 %I Cell Press %C Maryland Heights, MO %@ false