M
Maxim V. Kuleshov
Researcher at Icahn School of Medicine at Mount Sinai
Publications - 18
Citations - 7780
Maxim V. Kuleshov is an academic researcher from Icahn School of Medicine at Mount Sinai. The author has contributed to research in topics: Computer science & Gene. The author has an hindex of 8, co-authored 15 publications receiving 4402 citations. Previous affiliations of Maxim V. Kuleshov include Mount Sinai Health System.
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Journal ArticleDOI
Enrichr: a comprehensive gene set enrichment analysis web server 2016 update
Maxim V. Kuleshov,Matthew R. Jones,Andrew D. Rouillard,Nicolas F. Fernandez,Qiaonan Duan,Zichen Wang,Simon Koplev,Sherry L. Jenkins,Kathleen M. Jagodnik,Alexander Lachmann,Michael G. McDermott,Caroline D. Monteiro,Gregory W. Gundersen,Avi Ma'ayan +13 more
TL;DR: A significant update to one of the tools in this domain called Enrichr, a comprehensive resource for curated gene sets and a search engine that accumulates biological knowledge for further biological discoveries is presented.
Journal ArticleDOI
Gene Set Knowledge Discovery with Enrichr.
Zhuorui Xie,Allison Bailey,Maxim V. Kuleshov,Daniel J.B. Clarke,John Erol Evangelista,Sherry L. Jenkins,Alexander Lachmann,Megan L. Wojciechowicz,Eryk Kropiwnicki,Kathleen M. Jagodnik,Minji Jeon,Avi Ma'ayan +11 more
TL;DR: Enrichr as discussed by the authors is a gene set search engine that enables the querying of hundreds of thousands of annotated gene sets Enrichr uniquely integrates knowledge from many high-profile projects to provide synthesized information about mammalian genes and gene sets.
Journal ArticleDOI
The Library of Integrated Network-Based Cellular Signatures NIH Program: System-Level Cataloging of Human Cells Response to Perturbations
Alexandra B Keenan,Sherry L. Jenkins,Kathleen M. Jagodnik,Simon Koplev,Edward He,Denis Torre,Zichen Wang,Anders B. Dohlman,Moshe C. Silverstein,Alexander Lachmann,Maxim V. Kuleshov,Avi Ma'ayan,Vasileios Stathias,Raymond Terryn,Daniel J. Cooper,Michele Forlin,Amar Koleti,Dusica Vidovic,Caty Chung,Stephan C. Schürer,Jouzas Vasiliauskas,Marcin Pilarczyk,Behrouz Shamsaei,Mehdi Fazel,Yan Ren,Wen Niu,Nicholas A. Clark,Shana White,Naim Al Mahi,Lixia Zhang,Michal Kouril,John F. Reichard,Siva Sivaganesan,Mario Medvedovic,Jaroslaw Meller,Rick J. Koch,Marc R. Birtwistle,Ravi Iyengar,Eric A. Sobie,Evren U. Azeloglu,Julia A. Kaye,Jeannette Osterloh,Kelly Haston,Jaslin Kalra,Steve Finkbiener,Jonathan Z. Li,Pamela Milani,Miriam Adam,Renan Escalante-Chong,Karen Sachs,Alexander LeNail,Divya Ramamoorthy,Ernest Fraenkel,Gavin Daigle,Uzma Hussain,Alyssa Coye,Jeffrey D. Rothstein,Dhruv Sareen,Loren Ornelas,Maria G. Banuelos,Berhan Mandefro,Ritchie Ho,Clive N. Svendsen,Ryan G. Lim,Jennifer Stocksdale,Malcolm Casale,Terri G. Thompson,Jie Wu,Leslie M. Thompson,Victoria Dardov,Vidya Venkatraman,Andrea Matlock,Jennifer E. Van Eyk,Jacob D. Jaffe,Malvina Papanastasiou,Aravind Subramanian,Todd R. Golub,Sean D. Erickson,Mohammad Fallahi-Sichani,Marc Hafner,Nathanael S. Gray,Jia-Ren Lin,Caitlin E. Mills,Jeremy L. Muhlich,Mario Niepel,Caroline E. Shamu,Elizabeth H. Williams,David Wrobel,Peter K. Sorger,Laura M. Heiser,Joe W. Gray,James E. Korkola,Gordon B. Mills,Mark A. LaBarge,Mark A. LaBarge,Heidi S. Feiler,Mark A. Dane,Elmar Bucher,Michel Nederlof,Damir Sudar,Sean M. Gross,David Kilburn,Rebecca Smith,Kaylyn Devlin,Ron Margolis,Leslie Derr,Albert Lee,Ajay Pillai +107 more
TL;DR: The LINCS program focuses on cellular physiology shared among tissues and cell types relevant to an array of diseases, including cancer, heart disease, and neurodegenerative disorders.
Journal ArticleDOI
eXpression2Kinases (X2K) Web: linking expression signatures to upstream cell signaling networks.
Daniel J.B. Clarke,Maxim V. Kuleshov,Brian M. Schilder,Denis Torre,Mary E Duffy,Alexandra B Keenan,Alexander Lachmann,Axel S. Feldmann,Gregory W. Gundersen,Moshe C. Silverstein,Zichen Wang,Avi Ma'ayan +11 more
TL;DR: X2K Web is a new implementation of the original eXpression2Kinases algorithm with important enhancements, and includes many new transcription factor and kinase libraries, and PPI networks.
Journal ArticleDOI
The COVID-19 Drug and Gene Set Library.
Maxim V. Kuleshov,Dan J. Stein,Daniel J.B. Clarke,Eryk Kropiwnicki,Kathleen M. Jagodnik,Alon Bartal,John Erol Evangelista,Jason Hom,Minxuan Cheng,Allison Bailey,Abigail Zhou,Laura B. Ferguson,Alexander Lachmann,Avi Ma'ayan +13 more
TL;DR: The COVID-19 Drug and Gene Set Library can be used to identify community consensus, make researchers and clinicians aware of new potential therapies, enable machine-learning applications, and facilitate the research community to work together toward a cure.