David A. Knowles

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Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GoogleVerified email at eng.cam.ac.uk
Jonathan K PritchardStanford UniversityVerified email at stanford.edu
Stephen B MontgomeryAssociate Professor, Pathology and Genetics, Stanford UniversityVerified email at stanford.edu
Yang I LiUniversity of ChicagoVerified email at uchicago.edu
David GolanStatistics PhD student, Tel Aviv University.Verified email at post.tau.ac.il
Hae Kyung ImAssistant Professor, The University of ChicagoVerified email at uchicago.edu
Alvaro BarbeiraThe University of ChicagoVerified email at uchicago.edu
Yoav GiladUniversity of ChicagoVerified email at uchicago.edu
Konstantina PallaMSRVerified email at microsoft.com
Tim D SpectorGuys and St Thomas Hospital NHS Trust, Kings College LondonVerified email at kcl.ac.uk
Jack HumphreyInstructor, Mount Sinai School of MedicineVerified email at mssm.edu
Tom MinkaPrincipal Researcher, Microsoft Research, Cambridge UKVerified email at microsoft.com
Xin LiShanghai Institute of Nutrition and Health, Chinese Academy of Sciences (CAS)Verified email at sinh.ac.cn
Alexis BattleAssociate Professor, Biomedical Engineering, CS, Genetic Medicine at JHUVerified email at jhu.edu
Anshul KundajeAssistant Professor, Dept. of Genetics, Dept. of Computer Science, Stanford UniversityVerified email at stanford.edu
Thomas QuertermousProfessor of Medicine, Stanford UniversityVerified email at stanford.edu
Anil RajPrincipal Data Scientist, Calico LabsVerified email at calicolabs.com
Leopold PartsFaculty at Wellcome Sanger Institute; Senior Researcher (part-time) at University of TartuVerified email at sanger.ac.uk
Nasa Sinnott-ArmstrongStanford UniversityVerified email at stanford.edu
Michael WainbergCentre for Addiction and Mental Health; previously Stanford University and ISBVerified email at stanford.edu

David A. Knowles

Columbia University & New York Genome Center

Verified email at columbia.edu - Homepage

Machine learning Computational genomics


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Predicting splicing from primary sequence with deep learning K Jaganathan, SK Panagiotopoulou, JF McRae, SF Darbandi, D Knowles, ... Cell 176 (3), 535-548. e24, 2019	924	2019
Mapping cis- and trans-regulatory effects across multiple tissues in twins E Grundberg, KS Small, ÅK Hedman, AC Nica, A Buil, S Keildson, JT Bell, ... Nature genetics 44 (10), 1084-1089, 2012	844	2012
RNA splicing is a primary link between genetic variation and disease YI Li, B Van De Geijn, A Raj, DA Knowles, AA Petti, D Golan, Y Gilad, ... Science 352 (6285), 600-604, 2016	517	2016
Opportunities and challenges for transcriptome-wide association studies M Wainberg, N Sinnott-Armstrong, N Mancuso, AN Barbeira, DA Knowles, ... Nature genetics 51 (4), 592-599, 2019	481	2019
Annotation-free quantification of RNA splicing using LeafCutter YI Li, DA Knowles, J Humphrey, AN Barbeira, SP Dickinson, HK Im, ... Nature genetics 50 (1), 151-158, 2018	433	2018
Therapeutic reduction of ataxin-2 extends lifespan and reduces pathology in TDP-43 mice LA Becker, B Huang, G Bieri, R Ma, DA Knowles, P Jafar-Nejad, ... Nature 544 (7650), 367-371, 2017	418	2017
Global analysis of DNA methylation variation in adipose tissue from twins reveals links to disease-associated variants in distal regulatory elements E Grundberg, E Meduri, JK Sandling, ÅK Hedman, S Keildson, A Buil, ... The American Journal of Human Genetics 93 (5), 876-890, 2013	359	2013
Batch effects and the effective design of single-cell gene expression studies PY Tung, JD Blischak, CJ Hsiao, DA Knowles, JE Burnett, JK Pritchard, ... Scientific reports 7 (1), 39921, 2017	304	2017
Distinct epigenomic features in end-stage failing human hearts M Movassagh, MK Choy, DA Knowles, L Cordeddu, S Haider, T Down, ... Circulation 124 (22), 2411-2422, 2011	263	2011
Gene expression changes with age in skin, adipose tissue, blood and brain D Glass, A Viñuela, MN Davies, A Ramasamy, L Parts, D Knowles, ... Genome biology 14 (7), 1-12, 2013	261	2013
Fixed-form variational posterior approximation through stochastic linear regression T Salimans, DA Knowles	229	2013
Infer.NET 2.4 T Minka, J Winn, J Guiver, D Knowles Microsoft Research Cambridge http://research.microsoft.com/infernet, 2010	224*	2010
Infer.NET 2.5 T Minka, J Winn, J Guiver, D Knowles Microsoft Research Cambridge http://research.microsoft.com/infernet, 2012	190*	2012
Gaussian Process Regression Networks AG Wilson, DA Knowles, Z Ghahramani Proceedings of the 29th International Conference on Machine Learning (ICML 2011), 2011	184	2011
Molecular choreography of acute exercise K Contrepois, S Wu, KJ Moneghetti, D Hornburg, S Ahadi, MS Tsai, ... Cell 181 (5), 1112-1130. e16, 2020	180	2020
Infinite sparse factor analysis and infinite independent components analysis D Knowles, Z Ghahramani Independent Component Analysis and Signal Separation: 7th International …, 2007	164	2007
Nonparametric Bayesian sparse factor models with application to gene expression modeling D Knowles, Z Ghahramani	156	2011
Landscape of stimulation-responsive chromatin across diverse human immune cells D Calderon, MLT Nguyen, A Mezger, A Kathiria, F Müller, V Nguyen, ... Nature genetics 51 (10), 1494-1505, 2019	154	2019
Differential methylation of the TRPA1 promoter in pain sensitivity JT Bell, AK Loomis, LM Butcher, F Gao, B Zhang, CL Hyde, J Sun, H Wu, ... Nature communications 5 (1), 2978, 2014	140	2014
Non-conjugate Variational Message Passing for Multinomial and Binary Regression DA Knowles, TP Minka Advances in Neural Information Processing Systems, 2011	139	2011

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