In silico prediction of toxicity of non-congeneric industrial chemicals using ensemble learning based modeling approaches

Toxicology and Applied Pharmacology

Volumn 275, Issue 3, 2014, Pages 198-212

  Singh, Kunwar P ^a,b   Gupta, Shikha ^a,b  

^a ACADEMY OF SCIENTIFIC AND INNOVATIVE RESEARCH ACSIR   (India)

^b CSIR INDIAN INSTITUTE OF TOXICOLOGY RESEARCH   (India)

Author keywords

Diverse chemicals; Ensemble learning models; Interspecies model; Molecular descriptors; Regulatory toxicology; Toxicity

Indexed keywords

INDUSTRIAL CHEMICAL;

ACCURACY; ALGA; ALGORITHM; ARTICLE; CHEMICAL STRUCTURE; COMPUTER MODEL; DECISION TREE; MARINE BACTERIUM; NONHUMAN; PREDICTION; SPECIES; TETRAHYMENA PYRIFORMIS; TOXICITY; VALIDATION PROCESS;

ALGAE;

DIVERSE CHEMICALS; ENSEMBLE LEARNING MODELS; INTERSPECIES MODEL; MOLECULAR DESCRIPTORS; REGULATORY TOXICOLOGY; TOXICITY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; DECISION TREES; ENVIRONMENTAL MONITORING; LEAST-SQUARES ANALYSIS; MOLECULAR STRUCTURE; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; REGRESSION ANALYSIS; RISK ASSESSMENT; SPECIES SPECIFICITY; STOCHASTIC PROCESSES; TETRAHYMENA PYRIFORMIS; TOXICOLOGY;

EID: 84896725462     PISSN: 0041008X     EISSN: 10960333     Source Type: Journal    
DOI: 10.1016/j.taap.2014.01.006     Document Type: Article

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