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A Model of Visual Intelligent System for Genus Identification of Fish in the Siluriformes Order

IOP Conference Series: Earth and Environmental science 2021年第1期794卷

作者： Taufik Budhi Pramono R Ardharyan Islamy Saprudin Joni Johanda Putra Teddy Suparyanto Kartika Purwandari Tjeng Wawan Cenggoro Bens Pardamean Aquaculture Study Program Faculty of Fisheries and Marine Science Jenderal Soedirman University Purwokerto Central Java Indonesia 53123 Aquatic Resources Management Brawijaya University Malang East Java Indonesia Graduate Program Aquatic Resources Faculty of Fisheries and Marine Science Jenderal Soedirman University Purwokerto Central Java Indonesia 53123 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

Ambiguity in the fish naming is present in several fish species database, especially for fish in Siluformes order. To fix the ambiguity, a visual intelligent system is needed to automate the fish naming correction in the database. In this study, we developed a deep-learning-based model as the core of the intelligent system. The proposed model achieved 89% accuracy for the classification of three genera in Siluformes order: Mystus, Hemibagrus, and Glyptothorax.

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Organizing our knowledge of biodiversity

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Bulletin of the Association for Information science and Technology 2011年第4期37卷

作者： Hilmar Lapp Robert A. Morris Terry Catapano Donald Hobern Norman Morrison Assistant director of informatics National Evolutionary Synthesis Center (NESCent) Professor emeritus of computer science University of Massachusetts/Boston and biodiversity informatics staff Harvard University Herbaria librarian Columbia University Libraries and vice president Plazi Director Atlas of Living Australia and former TDWG chair Ontologies and data standards manager Natural Environment Research Council Environmental Bioinformatics Centre (NEBC) & The University of Manchester United Kingdom

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Single-cell landscape of innate and acquired drug resistance in acute myeloid leukemia

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Nature Communications 2024年第1期15卷 9402-9402页

作者： Wegmann, Rebekka Bonilla, Ximena Casanova, Ruben Chevrier, Stéphane Coelho, Ricardo Esposito, Cinzia Ficek-Pascual, Joanna Goetze, Sandra Gut, Gabriele Jacob, Francis Jacobs, Andrea Kuipers, Jack Lischetti, Ulrike Mena, Julien Milani, Emanuela S. Prummer, Michael Del Castillo, Jacobo Sarabia Singer, Franziska Sivapatham, Sujana Toussaint, Nora C. Vilinovszki, Oliver Wildschut, Mattheus H. E. Thavayogarajah, Tharshika Malani, Disha Zuend, Gregor Zoche, Martin Zimmermann, Marc Ziegler, Johanna Yu, Shuqing Wey, Norbert Wendt, Fabian Weller, Michael Weber, Walter P. Weber, Sandra Vlajnic, Tatjana Vetter, Marcus Van Drogen, Audrey Tusup, Marina Tuncel, Mustafa A. Tosevski, Vinko Tolnay, Markus Thomas, Tinu M. Tanna, Tanmay Stekhoven, Daniel J. Stark, Stefan Sreedharan, Vipin T. Sobottka, Bettina Snijder, Berend Shao, Wenguang Senti, Gabriela Schär, Tobias Schwan, Severin Schwalie, Petra C. Schlenker, Ramona Santacroce, Natascha Rätsch, Gunnar Rosano-González, María L. Rommel, Christian Ritter, Mathilde Rimmer, Natalie Prélot, Laurie Piscuoglio, Salvatore Pelkmans, Lucas Pedrioli, Patrick G. A. Lopez, Monica Nunez Nowak, Marta Nicolet, Stefan Ng, Charlotte K. Y. Murri, Riccardo Muenst, Simone Moch, Holger Miglino, Nicola Metzler, Julian M. Mehnert, Martin Markolin, Philipp Maass, Gerd Lugert, Sebastian Lombardo, Flavio C. Levesque, Mitchell Lehmann, Kjong-Van Kurzeder, Christian Kunze, Christian P. Kuebler, Werner Koelzer, Viktor H. Kahraman, Abdullah Kahles, André Jermann, Philip M. James, Alva R. Jahn, Katharina Jaeger, Tim M. Irmisch, Anja Immer, Alexander Huesser, Tamara Holtackers, Rene Herter, Sylvia Heinzelmann-Schwarz, Viola Haeuptle, Pirmin Günther, Detlef Grob, Linda Frey, Bruno Frei, Anja L. Ferreira, Pedro F. Fedier, André Eschbach, Katja Erkens, Martin Engler, Stefanie Dummer, Reinhard Drăgan, Monica-Andreea Davidson, Natalie R. Danenberg, Esther D’Costa, Maya Chicherova, Natalia Calgua, Byron Bosshard, Lars Bodenmiller, Bernd Bertolini, Anne Bernasconi, Lara Beisel, Christian Beerenwinkel, Niko Beck-Schim Institute of Molecular Systems Biology Department of Biology ETH Zurich Zurich Switzerland Department of Computer Science ETH Zurich Zurich Switzerland Department of Quantitative Biomedicine University of Zurich Zurich Switzerland Department of Biomedicine University Hospital Basel and University of Basel Basel Switzerland Institute of Molecular Life Sciences University of Zurich Zurich Switzerland Department of Health Sciences and Technology ETH Zurich Zurich Switzerland ETH PHRT Swiss Multi-Omics Center (SMOC) Lausanne Switzerland SIB Swiss Institute of Bioinformatics Lausanne Switzerland Department of Biosystems Science and Engineering ETH Zurich Zurich Switzerland NEXUS Personalized Health Technologies ETH Zurich Zurich Switzerland Swiss Data Science Center ETH Zürich Zurich Switzerland Department of Medical Oncology and Hematology University Hospital Zurich Zurich Switzerland Harvard Medical School and Dana-Farber Cancer Institute Boston United States Roche Pharmaceutical Research and Early Development Roche Innovation Center Zurich Zurich Switzerland Department of Pathology and Molecular Pathology University Hospital Zurich Zurich Switzerland University of Zurich Faculty of Medicine Zurich Switzerland Department of Dermatology University Hospital Zurich Zurich Switzerland AI Center at ETH Zurich Zurich Switzerland Institute of Medical Genetics and Pathology University Hospital Basel Basel Switzerland

Deep single-cell multi-omic profiling offers a promising approach to understand and overcome drug resistance in relapsed or refractory (rr) acute myeloid leukemia (AML). Here, we combine single-cell ex vivo drug profiling (pharmacoscopy) with single-cell and bulk DNA, RNA, and protein analyses, alongside clinical data from 21 rrAML patients. Unsupervised data integration reveals reduced ex vivo response to the Bcl-2 inhibitor venetoclax (VEN) in patients treated with both a hypomethylating agent (HMA) and VEN, compared to those pre-exposed to chemotherapy or HMA alone. Integrative analysis identifies both known and unreported mechanisms of innate and treatment-related VEN resistance and suggests alternative treatments, like targeting increased proliferation with the PLK inhibitor volasertib. Additionally, high CD36 expression in VEN-resistant blasts associates with sensitivity to CD36-targeted antibody treatment ex vivo. This study demonstrates how single-cell multi-omic profiling can uncover drug resistance mechanisms and treatment vulnerabilities, providing a valuable resource for future AML research. © 2024. The Author(s).

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Author Correction: mbDenoise: microbiome data denoising using zero-inflated probabilistic principal components analysis

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Genome biology 2023年第1期24卷 84页

作者： Yanyan Zeng Jing Li Chaochun Wei Hongyu Zhao Tao Wang Department of Bioinformatics and Biostatistics Shanghai Jiao Tong University Shanghai China. Department of Biostatistics Yale University New Haven CT USA. hongyu.zhao@yale.edu. SJTU-Yale Joint Center for Biostatistics and Data Science Shanghai Jiao Tong University Shanghai China. hongyu.zhao@yale.edu. Department of Bioinformatics and Biostatistics Shanghai Jiao Tong University Shanghai China. neowangtao@***. SJTU-Yale Joint Center for Biostatistics and Data Science Shanghai Jiao Tong University Shanghai China. neowangtao@***. Department of Statistics School of Mathematical Sciences Shanghai Jiao Tong University Shanghai China. neowangtao@***. Joint International Research Laboratory of Metabolic & Developmental Sciences Shanghai Jiao Tong University Shanghai China. neowangtao@***.

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Android-Based oil palm farmer’s income analysis to support precision agriculture

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AIP Conference Proceedings 2023年第1期2594卷

作者： M. P. Bimantio A. Ferhat L. Isnaini D. P. Putra T. Suparyanto B. Pardamean Department of Food and Agricultural Technology Institute of Agriculture STIPER Yogyakarta Indonesia 55281 Department of Agricultural Socio-Economics Institute of Agriculture STIPER Yogyakarta Indonesia 55281 Department of Agricultural Socio-Economics Gadjah Mada University Yogyakarta Indonesia 55281 Department of Agrotechnology Institute of Agriculture STIPER Yogyakarta Indonesia 55281 Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480

The purpose of this research is to create a simulator application in calculating farmer's income from the sale of fresh fruit bunches. Farmers can easily find out the outcomes based on how many kilograms of crops are sold through this application. This research was conducted in Mesuji Regency, Lampung Province, using primary data and descriptive analysis. The sampling technique utilized a proportional random sampling method and consisted of 88 oil palm farmers. The results indicated that the application made it simpler for farmers to find out their income. Farmers only needed to input the land area, the harvest number obtained on the harvest day that had been carried out, and the price of fresh fruit bunches so that they would know the estimated monthly and annual income calculations. These calculations can be used by farmers as a predicting and planning tool to avoid losses.

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Inhibition of colorectal cancer targets IL-6, CTLA-4, & B7-2 by Tislelizumab: molecular docking, dynamics, & STRING protein-protein network analysis

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Informatics in Medicine Unlocked 2023年 41卷

作者： Elkazzaz, Mahmoud Ullah, Shahid Gao, Tianshun Shamkh, Israa M. Ahmed, Amr Wu, Ted X. Elsharayidi, Maii S. Khan, Mohammad Shahbaz Rehman, Aziz-ur Lotfy, Marwa M. Haikal, Abdullah Abdalrahman, Mahmoud Department of Chemistry and Biochemistry Faculty of Science Damietta University Damietta 7952567 Egypt S Khan Lab Mardan Khyber Pakhtunkhwa Pakistan Big Data Center The Seventh Affiliated Hospital of Sun Yat-sen University Shenzhen 518107 China Botany and Microbiology Department Faculty of Science Cairo University Cairo 12613 Egypt Chemo and Bioinformatics Lab Bio Search Research Institution BSRI Giza 12613 Egypt Public Health Department First Health Cluster Ministry of Health Riyadh 966-11 Saudi Arabia Science Department Milton Academy Milton 02186 MA United States Central Public Health Laboratories Egyptian Ministry of Health Egypt Children's National Hospital Washington DC United States Keystone Pharmacogenomics LLC Bensalem 19020 PA United States Faculty of Pharmacy Zagazig University Zagazig 44511 Egypt Department of Pharmacognosy Faculty of Pharmacy Mansoura University Mansoura 35516 Egypt Lowell Institute CPS Northeastern University 360 Huntington Ave Boston 02115 MA United States

As a DNA mismatch repair deficit (dMMR) anticancer medication, and a humanized monoclonal antibody (hmAb), Tislelizumab has attracted significant interest in recent years. The programmed cell death protein-1 (PD-1) and its ligands (PD-L1/CD274/B7-H1 and PDL2/CD273) may bind to each other with great affinity. This binding prevents activated T-cells from continuing to proliferate, produce cytokines, and engage in cytotoxic action. The B7:PD-1 inhibitory immunological checkpoint receptor binds to the B7-2(CD86) B-lymphocyte activation antigen. This paper presents Tislelizumab's molecular docking and dynamics simulations with the receptor B7-2(CD86) and its downstream signaling proteins CTLA-4 and IL-6. When docked to B cell stimulatory factor-2 soluble IL-6 receptor alpha (sIL6Ra/CD126), Tislelizumab had a strong binding affinity of 329 kcal/mol and provided an excellent quality model with an LGscore of 4.54. The type I membrane protein B7-2(CD86), a member of the immunoglobulin superfamily, responded to docking with an affinity of −332.35 kcal/mol and LGscore of 2.54. Docking to the immune checkpoint protein receptor cytotoxic T-lymphocyte-associated protein-4 (CTLA-4/CD152) had a binding affinity of −305.91 kcal/mol, facilitating immunological control and cellular dissociation. Tislelizumab and these target proteins exhibited persistent and advantageous interactions in molecular dynamics studies. The STRING functional protein-protein network analysis supported our in silico docking and dynamic simulation results. This analysis also included comparisons of the binding modes of mAbs to protein receptors involved in the cancer hallmark mechanism(s), demonstrating that IL-6, B7-2, and CTLA-4 act and are inhibited in group-mode. Functional enrichment analysis and molecular modelling supported the relationship between the hallmarks of the tumor microenvironment that link inflammation to immunity. Tislelizumab may therefore be able to prevent these three proteins from actin

关键词： B7-2 Colorectal Cancer CTLA-4 Dostarlimab IL-6 Immunotherapy PD-1 Tislelizumab

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Author Correction: Genomic footprints of activated telomere maintenance mechanisms in cancer (Dec, 10.1038/s41467-019-13824-9, 2022)

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NATURE COMMUNICATIONS 2022年第1期13卷 1-1页

作者： Sieverling, Lina Hong, Chen Koser, Sandra D. Ginsbach, Philip Kleinheinz, Kortine Hutter, Barbara Braun, Delia M. Cortes-Ciriano, Isidro Xi, Ruibin Kabbe, Rolf Park, Peter J. Eils, Roland Schlesner, Matthias Brors, Benedikt Rippe, Karsten Jones, David T. W. Feuerbach, Lars Division of Applied Bioinformatics German Cancer Research Center (DKFZ) 69120 Heidelberg Germany Faculty of Biosciences Heidelberg University 69120 Heidelberg Germany Division of Applied Bioinformatics German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Biosciences Heidelberg University Heidelberg Germany Division of Theoretical Bioinformatics German Cancer Research Center (DKFZ) 69120 Heidelberg Germany Department for Bioinformatics and Functional Genomics Institute for Pharmacy and Molecular Biotechnology (IPMB) and BioQuant 69120 Heidelberg Germany Division of Theoretical Bioinformatics German Cancer Research Center (DKFZ) Heidelberg Germany Institute of Pharmacy and Molecular Biotechnology and BioQuant Heidelberg University Heidelberg Germany German Cancer Consortium (DKTK) Heidelberg Germany National Center for Tumor Diseases (NCT) Heidelberg Heidelberg Germany Heidelberg Center for Personalized Oncology (DKFZ-HIPO) German Cancer Research Center (DKFZ) Heidelberg Germany German Cancer Consortium (DKTK) German Cancer Research Center (DKFZ) Heidelberg Germany Division of Chromatin Networks German Cancer Research Center (DKFZ) and BioQuant 69120 Heidelberg Germany Department of Biomedical Informatics Harvard Medical School Boston Massachusetts 02115 USA Department of Chemistry Centre for Molecular Science Informatics University of Cambridge Cambridge CB2 1EW UK Ludwig Center at Harvard Medical School Boston Massachusetts 02115 USA Department of Biomedical Informatics Harvard Medical School Boston MA USA Department of Chemistry Centre for Molecular Science Informatics University of Cambridge Cambridge UK Ludwig Center at Harvard Medical School Boston MA USA School of Mathematical Sciences and Center for Statistical Science Peking University Beijing 100871 China Heidelberg University Heidelberg Germany New BIH Digital Health Center Berlin Institute of Health (BIH) and Charité - Universitätsmedizin Berlin Berlin Germany Bioi

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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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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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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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