Authors
Federica Eduati, Lara M Mangravite, Tao Wang, Hao Tang, J Christopher Bare, Ruili Huang, Thea Norman, Mike Kellen, Michael P Menden, Jichen Yang, Xiaowei Zhan, Rui Zhong, Guanghua Xiao, Menghang Xia, Nour Abdo, Oksana Kosyk, Stephen Friend, Allen Dearry, Anton Simeonov, Raymond R Tice, Ivan Rusyn, Fred A Wright, Gustavo Stolovitzky, Yang Xie, Julio Saez-Rodriguez
Publication date
2015/9
Journal
Nature biotechnology
Volume
33
Issue
9
Pages
933-940
Publisher
Nature Publishing Group UK
Description
The ability to computationally predict the effects of toxic compounds on humans could help address the deficiencies of current chemical safety testing. Here, we report the results from a community-based DREAM challenge to predict toxicities of environmental compounds with potential adverse health effects for human populations. We measured the cytotoxicity of 156 compounds in 884 lymphoblastoid cell lines for which genotype and transcriptional data are available as part of the Tox21 1000 Genomes Project. The challenge participants developed algorithms to predict interindividual variability of toxic response from genomic profiles and population-level cytotoxicity data from structural attributes of the compounds. 179 submitted predictions were evaluated against an experimental data set to which participants were blinded. Individual cytotoxicity predictions were better than random, with modest correlations …
Total citations
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