The applications of machine learning algorithms in the modeling of estrogen-like chemicals

Combinatorial Chemistry and High Throughput Screening

Volumn 12, Issue 5, 2009, Pages 490-496

  Liu, Huanxiang ^a,b   Yao, Xiaojun ^a   Gramatica, Paola ^b  

^a LANZHOU UNIVERSITY   (China)

^b UNIVERSITY OF INSUBRIA   (Italy)

Author keywords

Artificial neural networks; Classification; Estrogen like chemicals; Molecular descriptors; Quantitative structure activity relationships; Regression; Support vector machines; Validation

Indexed keywords

ENDOCRINE DISRUPTOR; ESTROGEN; ESTROGEN RECEPTOR;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; BIOLOGICAL ACTIVITY; MACHINE LEARNING; MOLECULAR MODEL; PREDICTION; PRIORITY JOURNAL; QUANTITATIVE STRUCTURE ACTIVITY RELATION; REVIEW; SCREENING; SUPPORT VECTOR MACHINE;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; ENDOCRINE DISRUPTORS; HUMANS; PROTEIN BINDING; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; RECEPTORS, ESTROGEN; REGRESSION ANALYSIS;

EID: 66849131413     PISSN: 13862073     EISSN: None     Source Type: Journal    
DOI: 10.2174/138620709788489037     Document Type: Review

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