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  Prediction of human population responses to toxic compounds by a collaborative competition

Eduati, F., Mangravite, L. M., Wang, T., Tang, H., Bare, J. C., Huang, R., et al. (2015). Prediction of human population responses to toxic compounds by a collaborative competition. Nat Biotechnol, 33(9), 933-940. doi:10.1038/nbt.3299.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-002A-38D4-D Version Permalink: http://hdl.handle.net/11858/00-001M-0000-002A-38D5-B
Genre: Journal Article

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© 2015 Macmillan Publishers Limited
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 Creators:
Eduati, F.1, Author
Mangravite, L. M.1, Author
Wang, T.1, Author
Tang, H.1, Author
Bare, J. C.1, Author
Huang, R.1, Author
Norman, T.1, Author
Kellen, M.1, Author
Menden, M. P.1, Author
Yang, J.1, Author
Zhan, X.1, Author
Zhong, R.1, Author
Xiao, G.1, Author
Xia, M.1, Author
Abdo, N.1, Author
Kosyk, O.1, Author
Collaboration, Niehs-Ncats-Unc Dream Toxicogenetics1, Author
van Bömmel, A.1, 2, Author              
Caffrey, B.1, 2, Author
Heinig, M.1, 2, Author              
Huska, M.1, 3, Author              Mammana, A.1, 4, Author              Perner, J.1, 3, Author              Vingron, M.5, Author              Friend, S.1, AuthorDearry, A.1, AuthorSimeonov, A.1, AuthorTice, R. R.1, AuthorRusyn, I.1, AuthorWright, F. A.1, AuthorStolovitzky, G.1, AuthorXie, Y.1, AuthorSaez-Rodriguez, J.1, Author more..
Affiliations:
1The NIEHS-NCATS-UNC DREAM Toxicogenetics Collaboration, ou_persistent22              
2Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1433547              
3IMPRS for Computational Biology and Scientific Computing - IMPRS-CBSC (Kirsten Kelleher), Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1479666              
4Computational Epigenetics (Ho-Ryun Chung), Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1479658              
5Gene regulation (Martin Vingron), Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1479639              

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 Abstract: 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 (Pearson's r < 0.28), consistent with complex trait genomic prediction. In contrast, predictions of population-level response to different compounds were higher (r < 0.66). The results highlight the possibility of predicting health risks associated with unknown compounds, although risk estimation accuracy remains suboptimal.

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Language(s): eng - English
 Dates: 2015-08-102015-09
 Publication Status: Published in print
 Pages: 8
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.1038/nbt.3299
ISSN: 1546-1696 (Electronic)1087-0156 (Print)
 Degree: -

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Title: Nat Biotechnol
Source Genre: Journal
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Publ. Info: Macmillan Publishers
Pages: - Volume / Issue: 33 (9) Sequence Number: - Start / End Page: 933 - 940 Identifier: -