Improving the prediction of organism-level toxicity through integration of chemical, protein target and cytotoxicity qHTS data.

ABSTRACT: Prediction of compound toxicity is essential because covering the vast chemical space requiring safety assessment using traditional experimentally-based, resource-intensive techniques is impossible. However, such prediction is nontrivial due to the complex causal relationship between compound structure and in vivo harm. Protein target annotations and in vitro experimental outcomes encode relevant bioactivity information complementary to chemicals' structures. This work tests the hypothesis that utilizing three complementary types of data will afford predictive models that outperform traditional models built using fewer data types. A tripartite, heterogeneous descriptor set for 367 compounds was comprised of (a) chemical descriptors, (b) protein target descriptors generated us

SUBMITTER: Allen CHG 

PROVIDER: S-EPMC6062365 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature