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Obesity alters pathology and treatment response in inflammatory disease

四川生理科学杂志 2022年第3期44卷 446-446页

作者： Sagar P Bapat NOMIS Center for Immunobiology and Microbial Pathogenesis The Salk Institute for Biological Studies La Jolla CA USA Gene Expression Laboratory The Salk Institute for Biological Studies La Jolla CA USA Medical Scientist Training Program University of California San Diego La Jolla CA USA Department of Laboratory Medicine University of California San Francisco San Francisco CA USA Department of Microbiology and Immunology University of California San Francisco San Francisco CA USA Diabetes Center University of California San Francisco San Francisco CA USA Medical Scientist Training Program University of California San Francisco CA USA Division of Pulmonary Critical Care Allergy and Sleep Department of Medicine University of California San Francisco San Francisco CA USA School of Pharmaceutical Sciences Xiamen University Xiamen China Department of Dermatology University of California San Diego La Jolla CA USA Department of Surgery University of California San Francisco San Francisco CA USA Department of Medicine University of California San Francisco San Francisco CA USA Sandler Asthma Basic Research Center University of California San Francisco San Francisco CA USA School of Medicine Wake Forest University Winston–Salem NC USA Department of Dermatology Icahn School of Medicine at Mount Sinai New York NY USA Lung Biology Center Department of Medicine University of California San Francisco San Francisco CA USA Department of Biomedical Science Graduate School Kyungpook National University Kyungpook National University Hospital Daegu South Korea Department of Dermatology University of California San Francisco San Francisco CA USA Department of Pathology University of California San Francisco San Francisco CA USA Department of Internal Medicine Division of Pulmonary Critical Care and Sleep Medicine University of Kentucky Lexington KY USA Pulmonary Critical Care Section Department of Medicine Veterans Affairs San Diego Hea

Decades of work have elucidated cytokine signalling and transcriptional pathways that control T cell differentiation and have led the way to targeted biologic therapies that are effective in a range of autoimmune,allergic and inflammatory *** evidence indicates that obesity and metabolic disease can also influence the immune system1-7,although the mechanisms and effects on immunotherapy outcomes remain largely ***,using two models of atopic dermatitis,we show that lean and obese mice mount markedly different immune *** converted the classical type 2 T helper(TH2)-predominant disease associated with atopic dermatitis to a more severe disease with prominent TH17 *** also observed divergent responses to biologic therapies targeting TH2 cytokines,which robustly protected lean mice but exacerbated disease in obese ***-cell RNA sequencing coupled with genome-wide binding analyses revealed decreased activity of nuclear receptor peroxisome proliferator-activated receptor-γ(PPARγ)in TH2 cells from obese mice relative to lean mice.

关键词： dermatitis inflammatory allergic

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Neuroprosthetics: Durable and Fatigue-Resistant Soft Peripheral Neuroprosthetics for In Vivo Bidirectional Signaling (Adv. Mater. 20/2021)

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Advanced Materials 2021年第20期33卷

作者： Hyunseon Seo Sang Ihn Han Kang-Il Song Duhwan Seong Kyungwoo Lee Sun Hong Kim Taesung Park Ja Hoon Koo Mikyung Shin Hyoung Won Baac Ok Kyu Park Soong Ju Oh Hyung-Seop Han Hojeong Jeon Yu-Chan Kim Dae-Hyeong Kim Taeghwan Hyeon Donghee Son School of Medicine Sungkyunkwan University Suwon 16419 Republic of Korea Center for Biomaterials Biomedical Research Institute Korea Institute of Science and Technology Seoul 02792 Republic of Korea Center for Nanoparticle Research Institute of Basic Science (IBS) Seoul 08826 Republic of Korea School of Chemical and Biological Engineering Seoul National University Seoul 08826 Republic of Korea Medical Device Development Center Daegu-Gyeongbuk Medical Innovation Foundation Daegu 41061 Republic of Korea Department of Electrical and Computer Engineering Sungkyunkwan University Suwon 16419 Republic of Korea Department of Electrical and Computer Engineering Inter-University Semiconductor Research Center Seoul National University Seoul 08826 Republic of Korea Department of Materials Science and Engineering Korea University Seoul 02841 Republic of Korea Interdisciplinary Program for Bioengineering Seoul National University Seoul 08826 Republic of Korea Department of Biomedical Engineering SKKU Institute for Convergence Sungkyunkwan University Suwon 16419 Republic of Korea Center for Neuroscience Imaging Research Institute for Basic Science (IBS) Suwon 16419 Republic of Korea Department of Superintelligence Engineering Sungkyunkwan University Suwon 16419 Republic of Korea

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QIIME 2 Enables Comprehensive End-to-End Analysis of Diverse Microbiome Data and Comparative Studies with Publicly Available Data

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Current Protocols in Bioinformatics 2020年第1期70卷 e100页

作者： Estaki, Mehrbod Jiang, Lingjing Bokulich, Nicholas A. McDonald, Daniel González, Antonio Kosciolek, Tomasz Martino, Cameron Zhu, Qiyun Birmingham, Amanda Vázquez-Baeza, Yoshiki Dillon, Matthew R. Bolyen, Evan Caporaso, J. Gregory Knight, Rob Department of Pediatrics University of California San Diego La Jolla CA United States Division of Biostatistics University of California San Diego La Jolla CA United States Center for Applied Microbiome Science Pathogen and Microbiome Institute Northern Arizona University Flagstaff AZ United States Department of Biological Sciences Northern Arizona University Flagstaff AZ United States Małopolska Centre of Biotechnology Jagiellonian University Kraków Poland Bioinformatics and Systems Biology Program University of California San Diego La Jolla CA United States Center for Microbiome Innovation University of California San Diego La Jolla CA United States Center for Computational Biology and Bioinformatics University of California San Diego La Jolla CA United States Jacobs School of Engineering University of California San Diego La Jolla CA United States Department of Computer Science and Engineering University of California San Diego La Jolla CA United States Department of Bioengineering University of California San Diego La Jolla CA United States

QIIME 2 is a completely re-engineered microbiome bioinformatics platform based on the popular QIIME platform, which it has replaced. QIIME 2 facilitates comprehensive and fully reproducible microbiome data science, improving accessibility to diverse users by adding multiple user interfaces. QIIME 2 can be combined with Qiita, an open-source web-based platform, to re-use available data for meta-analysis. The following basic protocol describes how to install QIIME 2 on a single computer and analyze microbiome sequence data, from processing of raw DNA sequence reads through generating publishable interactive figures. These interactive figures allow readers of a study to interact with data with the same ease as its authors, advancing microbiome science transparency and reproducibility. We also show how plug-ins developed by the community to add analysis capabilities can be installed and used with QIIME 2, enhancing various aspects of microbiome analyses—e.g., improving taxonomic classification accuracy. Finally, we illustrate how users can perform meta-analyses combining different datasets using readily available public data through Qiita. In this tutorial, we analyze a subset of the Early Childhood Antibiotics and the Microbiome (ECAM) study, which tracked the microbiome composition and development of 43 infants in the United States from birth to 2 years of age, identifying microbiome associations with antibiotic exposure, delivery mode, and diet. For more information about QIIME 2, see https://***. To troubleshoot or ask questions about QIIME 2 and microbiome analysis, join the active community at https://***. © 2020 The Authors. Basic Protocol: Using QIIME 2 with microbiome data. Support Protocol: Further microbiome analyses. © 2020 The Authors.

关键词： bioinformatics metagenomics microbiome QIIME 2 Qiita

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The repertoire of mutational signatures in human cancer (vol 578, pg 94, 2020)

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NATURE 2023年第7948期614卷 E41-E41页

作者： Alexandrov, Ludmil B. Kim, Jaegil Haradhvala, Nicholas J. Huang, Mi Ni Ng, Alvin Wei Tian Wu, Yang Boot, Arnoud Covington, Kyle R. Gordenin, Dmitry A. Bergstrom, Erik N. Islam, S. M. Ashiqul Lopez-Bigas, Nuria Klimczak, Leszek J. McPherson, John R. Morganella, Sandro Sabarinathan, Radhakrishnan Wheeler, David A. Mustonen, Ville Getz, Gad Rozen, Steven G. Stratton, Michael R. Department of Cellular and Molecular Medicine Department of Bioengineering Moores Cancer Center University of California San Diego CA USA Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Cellular and Molecular Medicine and Department of Bioengineering University of California San Diego La Jolla CA USA UC San Diego Moores Cancer Center San Diego CA USA University of California San Diego San Diego CA USA Broad Institute of MIT and Harvard Cambridge MA USA Center for Cancer Research Massachusetts General Hospital Boston MA USA Massachusetts General Hospital Boston MA USA Department of Pathology Massachusetts General Hospital Boston MA USA Harvard Medical School Boston MA USA Laboratory for Medical Science Mathematics RIKEN Center for Integrative Medical Sciences Yokohama Japan Computational Biology Program Ontario Institute for Cancer Research Toronto ON Canada Programme in Cancer & Stem Cell Biology Duke-NUS Medical School Singapore Singapore Centre for Computational Biology Duke-NUS Medical School Singapore Singapore Programme in Cancer and Stem Cell Biology Duke-NUS Medical School Singapore Singapore Programme in Cancer and Stem Cell Biology Centre for Computational Biology Duke-NUS Medical School Singapore Singapore SingHealth Duke-NUS Institute of Precision Medicine National Heart Centre Singapore Singapore Singapore Cancer Science Institute of Singapore National University of Singapore Singapore Singapore Institute of Molecular and Cell Biology Singapore Singapore Laboratory of Cancer Epigenome Division of Medical Science National Cancer Centre Singapore Singapore Singapore Duke-NUS Medical School Singapore Singapore Human Genome Sequencing Center Baylor College of Medicine Houston TX USA Dan L. Duncan Cancer Center Baylor College of Medicine Houston TX USA Department of Molecular and Human Genetics Baylor College of Medicine Houston TX USA Genome Integrity and Structural Biology Laboratory National Ins

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Silicone breast implant modification review: Overcoming capsular contracture

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Biomaterials Research 2018年第1期22卷 1-9页

作者： Shin, Byung Ho Kim, Byung Hwi Kim, Sujin Lee, Kangwon Choy, Young Bin Heo, Chan Yeong Seoul National University College of Medicine Department of Biomedical Engineering Seoul 03080 South Korea Seoul National University Department of Transdisciplinary Studies Graduate School of Convergence Science and Technology Seoul 08826 South Korea Seoul National University Interdisciplinary Program for Bioengineering College of Engineering Seoul 08826 South Korea Seoul National University Department of Plastic and Reconstructive Surgery College of Medicine Seoul 03080 South Korea Seoul National University Bundang Hospital Department of Plastic and Reconstructive Surgery Seongnam 13620 South Korea Seoul National University Institute of Medical and Biological Engineering Medical Research Center Seoul 03080 South Korea Advanced Institutes of Convergence Technology Suwon Gyeonggi-do 16229 South Korea

Background: Silicone implants are biomaterials that are frequently used in the medical industry due to their physiological inertness and low toxicity. However, capsular contracture remains a concern in long-term transplantation. To date, several studies have been conducted to overcome this problem. This review summarizes and explores these trends. Main body: First, we examined the overall foreign body response from initial inflammation to fibrosis capsule formation in detail and introduced various studies to overcome capsular contracture. Secondly, we introduced that the main research approaches are to inhibit fibrosis with anti-inflammatory drugs or antibiotics, to control the topography of the surface of silicone implants, and to administer plasma treatment. Each study examined aspects of the various mechanisms by which capsular contracture could occur, and addressed the effects of inhibiting fibrosis. Conclusion: This review introduces various silicone surface modification methods to date and examines their limitations. This review will help identify new directions in inhibiting the fibrosis of silicone implants. © 2018 The Author(s).

关键词： Capsular contracture Fibrosis Foreign body reaction Inflammation Modification Silicone implant

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TDP-43 loss and ALS-risk SNPs drive mis-splicing and depletion of UNC13A (vol 603, pg 131, 2022)

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NATURE 2024年第8020期631卷 E7-E7页

作者： Brown, Anna-Leigh Wilkins, Oscar G. Keuss, Matthew J. Hill, Sarah E. Zanovello, Matteo Lee, Weaverly Colleen Bampton, Alexander Lee, Flora C. Y. Masino, Laura Qi, Yue A. Bryce-Smith, Sam Gatt, Ariana Hallegger, Martina Fagegaltier, Delphine Phatnani, Hemali Phatnani, Hemali Newcombe, Jia Gustavsson, Emil K. Seddighi, Sahba Reyes, Joel F. Coon, Steven L. Ramos, Daniel Schiavo, Giampietro Fisher, Elizabeth M. C. Raj, Towfique Secrier, Maria Lashley, Tammaryn Ule, Jernej Buratti, Emanuele Humphrey, Jack Ward, Michael E. Fratta, Pietro UCL Queen Square Motor Neuron Disease Centre Department of Neuromuscular Diseases UCL Queen Square Institute of Neurology UCL London UK The Francis Crick Institute London UK UK Dementia Research Institute University College London London UK Department of Molecular Biology and Nanobiotechnology National Institute of Chemistry Ljubljana Slovenia National Institute of Neurological Disorders and Stroke NIH Bethesda MD USA Medical Scientist Training Program Johns Hopkins University School of Medicine Baltimore MD USA Center for Alzheimer’s and Related Dementias National Institutes of Health Bethesda MD USA Queen Square Brain Bank UCL Queen Square Institute of Neurology University College London London UK Department of Neurodegenerative Disease UCL Queen Square Institute of Neurology University College London London UK Great Ormond Street Institute of Child Health Genetics and Genomic Medicine University College London London UK Center for Genomics of Neurodegenerative Disease New York Genome Center (NYGC) New York NY USA NeuroResource Department of Neuroinflammation UCL Queen Square Institute of Neurology London UK Molecular Genomics Core Eunice Kennedy Shriver National Institute of Child Health and Human Development NIH Bethesda MD USA Nash Family Department of Neuroscience and Friedman Brain Institute Icahn School of Medicine at Mount Sinai New York NY USA Ronald M. Loeb Center for Alzheimer’s Disease Icahn School of Medicine at Mount Sinai New York NY USA Department of Pathology Fishberg Department of Neuroscience Icahn School of Medicine at Mount Sinai New York NY USA Department of Genetics and Genomic Sciences and Icahn Institute for Data Science and Genomic Technology Icahn School of Medicine at Mount Sinai New York NY USA Estelle and Daniel Maggin Department of Neurology Icahn School of Medicine at Mount Sinai New York NY USA Department of Genetics Evolution and Environment UCL Genetics Institute University College London London UK Mole

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The evolutionary history of 2,658 cancers (vol 578, pg 122, 2020)

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NATURE 2023年第7948期614卷 E42-E42页

作者： Gerstung, Moritz Jolly, Clemency Leshchiner, Ignaty Dentro, Stefan C. Gonzalez, Santiago Rosebrock, Daniel Mitchell, Thomas J. Rubanova, Yulia Anur, Pavana Yu, Kaixian Tarabichi, Maxime Deshwar, Amit Wintersinger, Jeff Kleinheinz, Kortine Vazquez-Garcia, Ignacio Haase, Kerstin Jerman, Lara Sengupta, Subhajit Macintyre, Geoff Malikic, Salem Donmez, Nilgun Livitz, Dimitri G. Cmero, Marek Demeulemeester, Jonas Schumacher, Steven Fan, Yu Yao, Xiaotong Lee, Juhee Schlesner, Matthias Boutros, Paul C. Bowtell, David D. Zhu, Hongtu Getz, Gad Imielinski, Marcin Beroukhim, Rameen Sahinalp, S. Cenk Ji, Yuan Peifer, Martin Markowetz, Florian Mustonen, Ville Yuan, Ke Wang, Wenyi Morris, Quaid D. Spellman, Paul T. Wedge, David C. Van Loo, Peter European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) Cambridge UK European Molecular Biology Laboratory Genome Biology Unit Heidelberg Germany Wellcome Sanger Institute Cambridge UK Genome Biology Unit European Molecular Biology Laboratory (EMBL) Heidelberg Germany University of Ljubljana Ljubljana Slovenia The Francis Crick Institute London UK Big Data Institute University of Oxford Oxford UK Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Big Data Institute Li Ka Shing Centre University of Oxford Oxford UK University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Department of Applied Mathematics and Theoretical Physics Centre for Mathematical Sciences University of Cambridge Cambridge UK Department of Epidemiology and Biostatistics Memorial Sloan Kettering Cancer Center New York NY USA Department of Statistics Columbia University New York NY USA Department of Haematology University of Cambridge Cambridge UK University of Leuven Leuven Belgium Broad Institute of MIT and Harvard Cambridge MA USA Center for Cancer Research Massachusetts General Hospital Charlestown MA USA Department of Pathology Massachusetts General Hospital Boston MA USA Harvard Medical School Boston MA USA Center for Cancer Research Massachusetts General Hospital Boston MA USA Dana-Farber Cancer Institute Boston MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Oxford NIHR Biomedical Research Centre Oxford UK Oxford NIHR Biomedical Research Centre University of Oxford Oxford UK University of Toronto Toronto Ontario Canada Vector Institute Toronto Ontario Canada Vector Institute Toronto ON Canada Department of Computer Science University of Toronto Toronto ON Canada Ontario Institute for Cancer Research Toronto Ontario Canada University of California Los Angeles

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Patterns of somatic structural variation in human cancer genomes (vol 578, pg 112, 2020)

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NATURE 2023年第7948期614卷 E38-E38页

作者： Li, Yilong Roberts, Nicola D. Wala, Jeremiah A. Shapira, Ofer Schumacher, Steven E. Kumar, Kiran Khurana, Ekta Waszak, Sebastian Korbel, Jan O. Haber, James E. Imielinski, Marcin Weischenfeldt, Joachim Beroukhim, Rameen Campbell, Peter J. Cancer Genome Project Wellcome Trust Sanger Institute Hinxton UK Totient Inc Cambridge MA USA Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Haematology University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Korea Advanced Institute of Science and Technology Daejeon South Korea Department of Zoology Genetics and Physical Anthropology University of Santiago de Compostela Santiago de Compostela Spain Centre for Research in Molecular Medicine and Chronic Diseases (CIMUS) University of Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) University of Vigo Vigo Spain Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain Department of Zoology Genetics and Physical Anthropology (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) Universidade de Vigo Vigo Spain The Broad Institute of Harvard and MIT Cambridge MA USA Bioinformatics and Integrative Genomics Harvard University Cambridge MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Broad Institute of MIT and Harvard Cambridge MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Harvard Medical School Boston MA USA Massachusetts General Hospital Center for Cancer Research Charlestown MA USA Dana-Farber Cancer Institute Boston MA USA Department of Biostatistics and Computational Biology Dana-Farber Cancer Institute and Harvard Medical School Boston MA USA Weill Cornell Medical College New York NY USA Department of Physiology and Biophysics Weill Cornell Medicine New York NY USA Institute for Computational Biomedicine Weill Cornell Medicine New York NY USA Controlled Department and Institution New York NY USA Englander Institute for Precision Medicine Weill Cornell Medicine Ne

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SARS-CoV-2 identified through crystallographic screening and computational docking

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science Advances 2021年第16期7卷

作者： Schuller, Marion Correy, Galen J. Gahbauer, Stefan Fearon, Daren Wu, Taiasean Díaz, Roberto Efraín Young, Iris D. Martins, Luan Carvalho Smith, Dominique H. Schulze-Gahmen, Ursula Owens, Tristan W. Deshpande, Ishan Merz, Gregory E. Thwin, Aye C. Biel, Justin T. Peters, Jessica K. Moritz, Michelle Herrera, Nadia Kratochvil, Huong T. Aimon, Anthony Bennett, James M. Neto, Jose Brandao Cohen, Aina E. Dias, Alexandre Douangamath, Alice Dunnett, Louise Fedorov, Oleg Ferla, Matteo P. Fuchs, Martin R. Gorrie-Stone, Tyler J. Holton, James M. Johnson, Michael G. Krojer, Tobias Meigs, George Powell, Ailsa J. Rack, Johannes Gregor Matthias Rangel, Victor L. Russi, Silvia Skyner, Rachael E. Smith, Clyde A. Soares, Alexei S. Wierman, Jennifer L. Zhu, Kang O Brien, Peter Jura, Natalia Ashworth, Alan Irwin, John J. Thompson, Michael C. Gestwicki, Jason E. Von Delft, Frank Shoichet, Brian K. Fraser, James S. Ahel, Ivan Sir William Dunn School of Pathology University of Oxford South Parks Road OxfordOX1 3RE United Kingdom Department of Bioengineering and Therapeutic Sciences University of California San Francisco San FranciscoCA94158 United States Department of Pharmaceutical Chemistry University of California San Francisco San FranciscoCA94158 United States Diamond Light Source Ltd. Harwell Science and Innovation Campus DidcotOX11 0DE United Kingdom Institute for Neurodegenerative Disease University of California San Francisco San FranciscoCA94158 United States Chemistry and Chemical Biology Graduate Program University of California San Francisco San FranciscoCA94158 United States Tetrad Graduate Program University of California San Francisco San FranciscoCA94158 United States Coronavirus Research Group Structural Biology Consortium University of California San Francisco San FranciscoCA94158 United States Biochemistry Department Institute for Biological Sciences Federal University of Minas Gerais Belo Horizonte Brazil Helen Diller Family Comprehensive Cancer University of California San Francisco San FranciscoCA94158 United States Centre for Medicines Discovery University of Oxford South Parks Road HeadingtonOX3 7DQ United Kingdom Stanford Synchrotron Radiation Lightsource Slac National Accelerator Center Menlo ParkCA94025 United States Wellcome Centre for Human Genetics University of Oxford Old Road Campus OxfordOX3 7BN United Kingdom National Synchrotron Light Source Ii Brookhaven National Laboratory UptonNY11973 United States Department of Biochemistry and Biophysics University of California San Francisco San FranciscoCA94158 United States Department of Molecular Biophysics and Integrated Bioimaging Lawrence Berkeley National Laboratory BerkeleyCA94720 United States ChemPartner Corporation South San FranciscoCA94080 United States Structural Genomics Consortium University of Oxford Old Road Campus HeadingtonOX3 7DQ United Kingdom School of

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) macrodomain within the nonstructural protein 3 counteracts host-mediated antiviral adenosine diphosphate ribosylation signaling. This enzyme is a promising antiviral target because catalytic mutations render viruses nonpathogenic. Here, we report a massive crystallographic screening and computational docking effort, identifying new chemical matter primarily targeting the active site of the macrodomain. Crystallographic screening of 2533 diverse fragments resulted in 214 unique macrodomain-binders. An additional 60 molecules were selected from docking more than 20 million fragments, of which 20 were crystallographically confirmed. X-ray data collection to ultra-high resolution and at physiological temperature enabled assessment of the conformational heterogeneity around the active site. Several fragment hits were confirmed by solution binding using three biophysical techniques (differential scanning fluorimetry, homogeneous time-resolved fluorescence, and isothermal titration calorimetry). The 234 fragment structures explore a wide range of chemotypes and provide starting points for development of potent SARS-CoV-2 macrodomain inhibitors. © 2021 American Association for the Advancement of science. All rights reserved.

关键词： Coronavirus

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Genomic basis for RNA alterations in cancer (vol 578, pg 129, 2020)

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NATURE 2023年第7948期614卷 E37-E37页

作者： Calabrese, Claudia Davidson, Natalie R. Demircioglu, Deniz Fonseca, Nuno A. He, Yao Lehmann, Kjong-Van Liu, Fenglin Shiraishi, Yuichi Soulette, Cameron M. Urban, Lara Greger, Liliana Li, Siliang Liu, Dongbing Perry, Marc D. Xiang, Qian Zhang, Fan Zhang, Junjun Bailey, Peter Erkek, Serap Hoadley, Katherine A. Hou, Yong Huska, Matthew R. Kilpinen, Helena Korbel, Jan O. Marin, Maximillian G. Markowski, Julia Nandi, Tannistha Pan-Hammarstrom, Qiang Pedamallu, Chandra Sekhar Siebert, Reiner Stark, Stefan G. Su, Hong Tan, Patrick Waszak, Sebastian M. Yung, Christina Zhu, Shida Awadalla, Philip Creighton, Chad J. Meyerson, Matthew Ouellette, B. F. Francis Wu, Kui Yang, Huanming Brazma, Alvis Brooks, Angela N. Goke, Jonathan Ratsch, Gunnar Schwarz, Roland F. Stegle, Oliver Zhang, Zemin European Molecular Biology Laboratory European Bioinformatics Institute Hinxton UK European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) Cambridge UK Genome Biology Unit European Molecular Biology Laboratory (EMBL) Heidelberg Germany CIBIO/InBIO - Research Center in Biodiversity and Genetic Resources Universidade do Porto Vairão Portugal Berlin Institute for Medical Systems Biology Max Delbruck Center for Molecular Medicine Berlin Germany German Cancer Consortium (DKTK) partner site Berlin Germany German Cancer Research Center (DKFZ) Heidelberg Germany Berlin Institute for Medical Systems Biology Max Delbrück Center for Molecular Medicine Berlin Germany German Cancer Consortium (DKTK) Partner site Berlin Berlin Germany European Molecular Biology Laboratory Genome Biology Unit Heidelberg Germany Division of Computational Genomics and Systems Genetics German Cancer Research Center (DKFZ) Heidelberg Germany ETH Zurich Zurich Switzerland Memorial Sloan Kettering Cancer Center New York NY USA Weill Cornell Medical College New York NY USA SIB Swiss Institute of Bioinformatics Lausanne Switzerland University Hospital Zurich Zurich Switzerland Computational Biology Center Memorial Sloan Kettering Cancer Center New York NY USA Department of Biology ETH Zurich Zürich Switzerland Department of Computer Science ETH Zurich Zurich Switzerland Korea University Seoul South Korea Computational and Systems Biology Program Memorial Sloan Kettering Cancer Center New York NY USA Department of Physiology and Biophysics Weill Cornell Medicine New York NY USA Institute for Computational Biomedicine Weill Cornell Medicine New York NY USA Controlled Department and Institution New York NY USA Englander Institute for Precision Medicine Weill Cornell Medicine New York NY USA National University of Singapore Singapore Singapore Genome Institute of Singapore Singapore Singapore Computational and Systems Biology Genome Institute of Singap

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