Decision tree models for data mining in hit discovery

Expert Opinion on Drug Discovery

Volumn 7, Issue 4, 2012, Pages 341-352

  Hammann, Felix ^a   Drewe, Juergen ^b  

^a UNIVERSITY OF BASEL   (Switzerland)

^b UNIVERSITY HOSPITAL BASEL   (Switzerland)

Author keywords

decision tree; DTI; QSAR; rule based systems

Indexed keywords

CYTOCHROME P450; CYTOCHROME P450 1A2; CYTOCHROME P450 INHIBITOR; GLYCOPROTEIN P; NONNUCLEOSIDE REVERSE TRANSCRIPTASE INHIBITOR;

ANTIBACTERIAL ACTIVITY; ANTIFUNGAL ACTIVITY; ARTIFICIAL NEURAL NETWORK; AUTOMATION; BLOOD BRAIN BARRIER; CHI SQUARE TEST; CLASSIFICATION ALGORITHM; COMPUTER MODEL; COMPUTER PROGRAM; CORRELATION COEFFICIENT; DATA BASE; DATA MINING; DECISION TREE; DRUG ABSORPTION; DRUG DEVELOPMENT; DRUG DISTRIBUTION; DRUG DOSE REGIMEN; DRUG ELIMINATION; DRUG METABOLISM; DRUG RESEARCH; ENZYME INHIBITION; HIGH THROUGHPUT SCREENING; IC 50; NEUROTOXICITY; PRACTICE GUIDELINE; PREDICTIVE VALUE; PRIORITY JOURNAL; QUALITY CONTROL; QUANTITATIVE STRUCTURE ACTIVITY RELATION; REVIEW; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; DATA MINING; DECISION TREES; DRUG DISCOVERY; HIGH-THROUGHPUT SCREENING ASSAYS; HUMANS; INFORMATION STORAGE AND RETRIEVAL; MODELS, THEORETICAL; PHARMACOKINETICS; SMALL MOLECULE LIBRARIES; SOFTWARE;

EID: 84859338757     PISSN: 17460441     EISSN: 1746045X     Source Type: Journal    
DOI: 10.1517/17460441.2012.668182     Document Type: Review

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