Substructure-based support vector machine classifiers for prediction of adverse effects in diverse classes of drugs

Journal of Chemical Information and Modeling

Volumn 46, Issue 6, 2006, Pages 2478-2486

  Bhavani, S ^a   Nagargadde, A ^a   Thawani, A ^a   Sridhar, V ^a   Chandra, N ^b  

^a Satyam Computer Services Ltd India   (India)

^b INDIAN INSTITUTE OF SCIENCE   (India)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTATIONAL METHODS; DATA ACQUISITION; DATABASE SYSTEMS; DRUG THERAPY; ENCODING (SYMBOLS);

SCREENING DATA; SUPPORT VECTOR MACHINES; TORSADE DE POINTES (TDP); TORSADOGENICITY;

DRUG PRODUCTS;

CARCINOGEN;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; BIOLOGY; CHEMICAL MODEL; CHEMICALLY INDUCED DISORDER; CHEMISTRY; COMPUTER PROGRAM; DRUG INDUSTRY; DRUG SCREENING; HUMAN; INSTRUMENTATION; METHODOLOGY; ROC CURVE; SEQUENCE ANALYSIS; STATISTICAL MODEL; TORSADE DES POINTES;

ALGORITHMS; CARCINOGENS; CHEMISTRY, PHARMACEUTICAL; COMPUTATIONAL BIOLOGY; DRUG EVALUATION, PRECLINICAL; DRUG INDUSTRY; HUMANS; MODELS, CHEMICAL; MODELS, STATISTICAL; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED; ROC CURVE; SEQUENCE ANALYSIS, PROTEIN; SOFTWARE; TORSADES DE POINTES;

EID: 33845772315     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci0601281     Document Type: Article

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