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Deepak Sharma

Alumni

Publications

RECOVER identifies synergistic drug combinations in vitro through sequential model optimization
Thomas Gaudelet
Andrew Anighoro
Torsten Gross
Francisco Martínez-Peña
Eileen L. Tang
M.S. Suraj
Cristian Regep
Jeremy B.R. Hayter
Nicholas Valiante
Mike Tyers
Charles E.S. Roberts
Michael M. Bronstein
Luke L. Lairson
Jake P. Taylor-King
RECOVER: sequential model optimization platform for combination drug repurposing identifies novel synergistic compounds in vitro
Thomas Gaudelet
Andrew Anighoro
Torsten Gross
Francisco Martínez-Peña
Eileen L. Tang
S. SurajM
Cristian Regep
Jeremy B.R. Hayter
N. Valiante
Almer M. van der Sloot
Mike Tyers
Charles E.S. Roberts
Michael M. Bronstein
Luke Lee Lairson
Jake P. Taylor-King
Deep interpretability for GWAS
Louis-philippe Lemieux Perreault
Audrey Lemaccon
Marie-Pierre Dub'e
Genome-Wide Association Studies are typically conducted using linear models to find genetic variants associated with common diseases. In the… (voir plus)se studies, association testing is done on a variant-by-variant basis, possibly missing out on non-linear interaction effects between variants. Deep networks can be used to model these interactions, but they are difficult to train and interpret on large genetic datasets. We propose a method that uses the gradient based deep interpretability technique named DeepLIFT to show that known diabetes genetic risk factors can be identified using deep models along with possibly novel associations.