E
Evan M. Cofer
Researcher at Princeton University
Publications - 15
Citations - 1707
Evan M. Cofer is an academic researcher from Princeton University. The author has contributed to research in topics: Deep learning & Drosophila melanogaster. The author has an hindex of 5, co-authored 14 publications receiving 1186 citations. Previous affiliations of Evan M. Cofer include Joslin Diabetes Center & Trinity University.
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Journal ArticleDOI
Opportunities and obstacles for deep learning in biology and medicine.
Travers Ching,Daniel Himmelstein,Brett K. Beaulieu-Jones,Alexandr A. Kalinin,Brian T. Do,Gregory P. Way,Enrico Ferrero,Paul-Michael Agapow,Michael Zietz,Michael M. Hoffman,Michael M. Hoffman,Wei Xie,Gail L. Rosen,Benjamin J. Lengerich,Johnny Israeli,Jack Lanchantin,Stephen Woloszynek,Anne E. Carpenter,Avanti Shrikumar,Jinbo Xu,Evan M. Cofer,Evan M. Cofer,Christopher A. Lavender,Srinivas C. Turaga,Amr Alexandari,Zhiyong Lu,David J. Harris,Dave DeCaprio,Yanjun Qi,Anshul Kundaje,Yifan Peng,Laura K. Wiley,Marwin H. S. Segler,Simina M. Boca,S. Joshua Swamidass,Austin Huang,Anthony Gitter,Anthony Gitter,Casey S. Greene +38 more
TL;DR: It is found that deep learning has yet to revolutionize biomedicine or definitively resolve any of the most pressing challenges in the field, but promising advances have been made on the prior state of the art.
Journal ArticleDOI
Selene: a PyTorch-based deep learning library for sequence data
TL;DR: Selene is a deep learning library that enables the expansion of existing deep learning models to new data, the development of new model architectures, and the evaluation of these new models on biological sequence data.
Posted ContentDOI
Opportunities And Obstacles For Deep Learning In Biology And Medicine
Travers Ching,Daniel Himmelstein,Brett K. Beaulieu-Jones,Alexandr A. Kalinin,Brian T. Do,Gregory P. Way,Enrico Ferrero,Paul-Michael Agapow,Wei Xie,Gail L. Rosen,Benjamin J. Lengerich,Johnny Israeli,Jack Lanchantin,Stephen Woloszynek,Anne E. Carpenter,Avanti Shrikumar,Jinbo Xu,Evan M. Cofer,David J. Harris,Dave DeCaprio,Yanjun Qi,Anshul Kundaje,Yifan Peng,Laura K. Wiley,Marwin H. S. Segler,Anthony Gitter,Casey S. Greene +26 more
TL;DR: This work examines applications of deep learning to a variety of biomedical problems -- patient classification, fundamental biological processes, and treatment of patients -- to predict whether deep learning will transform these tasks or if the biomedical sphere poses unique challenges.
Journal ArticleDOI
A systematic machine learning and data type comparison yields metagenomic predictors of infant age, sex, breastfeeding, antibiotic usage, country of origin, and delivery type.
Alan Le Goallec,Braden T. Tierney,Jacob M. Luber,Evan M. Cofer,Aleksandar Kostic,Aleksandar Kostic,Chirag J. Patel +6 more
TL;DR: A framework for building microbiome-derived indicators of host phenotype by comparing prediction performances and biological interpretation across 8 machine learning methods and 4 different types of metagenomic data is proposed.
Ten Quick Tips for Deep Learning in Biology
Benjamin D. Lee,Benjamin D. Lee,Anthony Gitter,Anthony Gitter,Casey S. Greene,Casey S. Greene,Sebastian Raschka,Finlay Maguire,Alexander J. Titus,Michael D. Kessler,Michael D. Kessler,Alexandra J. Lee,Marc G. Chevrette,Paul Allen Stewart,Thiago Britto-Borges,Evan M. Cofer,Kun-Hsing Yu,Kun-Hsing Yu,Juan Carmona,Elana J. Fertig,Alexandr A. Kalinin,Beth Signal,Benjamin J. Lengerich,Timothy J. Triche,Timothy J. Triche,Timothy J. Triche,Simina M. Boca +26 more
TL;DR: This research highlights the need to understand more fully the role of language in the decision-making process and the role that language plays in the development of knowledge and identity.