Use of in Vitro HTS-Derived Concentration–Response Data as Biological Descriptors Improves the Accuracy of QSAR Models of in Vivo Toxicity | Zendy

Alexander Sedykh | Zendy; Hao Zhu | Zendy; Hao Tang | Zendy; Liying Zhang | Zendy; Ann M. Richard | Zendy; Ivan Rusyn | Zendy; Alexander Tropsha | Zendy

Open Access

Use of in Vitro HTS-Derived Concentration–Response Data as Biological Descriptors Improves the Accuracy of QSAR Models of in Vivo Toxicity

Author(s) -

Alexander Sedykh,

Hao Zhu,

Hao Tang,

Liying Zhang,

Ann M. Richard,

Ivan Rusyn,

Alexander Tropsha

Publication year - 2010

Publication title -

environmental health perspectives

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.257

H-Index - 282

eISSN - 1552-9924

pISSN - 0091-6765

DOI - 10.1289/ehp.1002476

Subject(s) - quantitative structure–activity relationship , applicability domain , pubchem , random forest , test set , computer science , data set , biological system , computational biology , machine learning , artificial intelligence , biology

Quantitative high-throughput screening (qHTS) assays are increasingly being used to inform chemical hazard identification. Hundreds of chemicals have been tested in dozens of cell lines across extensive concentration ranges by the National Toxicology Program in collaboration with the National Institutes of Health Chemical Genomics Center.

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