Leveraging high-throughput screening data, deep neural networks, and conditional generative adversarial networks to advance predictive toxicology.

Leveraging high-throughput screening data, deep neural networks, and conditional generative adversarial networks to advance predictive toxicology.

There are currently 85,000 chemicals registered with the Environmental Protection Agency (EPA) under the Toxic Substances Control Act, but only a small fraction have measured toxicological data. To address this gap, high-throughput screening (HTS) and computational methods are vital. As part of one...

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Bibliographic Details
Main Authors:	Adrian J Green, Martin J Mohlenkamp, Jhuma Das, Meenal Chaudhari, Lisa Truong, Robyn L Tanguay, David M Reif
Format:	Article
Language:	English
Published:	Public Library of Science (PLoS) 2021-07-01
Series:	PLoS Computational Biology
Online Access:	https://doi.org/10.1371/journal.pcbi.1009135

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