P-glycoprotein substrate models using support vector machines based on a comprehensive data set

Journal of Chemical Information and Modeling

Volumn 51, Issue 6, 2011, Pages 1447-1456

  Wang, Zhi ^a,b   Chen, Yuanying ^a   Liang, Hu ^a   Bender, Andreas ^b   Glen, Robert C ^b   Yan, Aixia ^a  

^a BEIJING UNIVERSITY OF CHEMICAL TECHNOLOGY   (China)

^b UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

CYTOLOGY; FORECASTING; GLYCOPROTEINS; STEREOCHEMISTRY; SUPPORT VECTOR MACHINES;

COMPUTATIONAL MODEL; CORRELATION COEFFICIENT; HIGHER FREQUENCIES; LEAVE-ONE-OUT CROSS VALIDATIONS; MODEL-BASED OPC; PREDICTION ACCURACY; RELIABLE MODELS; REVERSE TRANSCRIPTASES;

SUBSTRATES;

GLYCOPROTEIN P;

ARTICLE; ARTIFICIAL INTELLIGENCE; BIOLOGY; METABOLISM; METHODOLOGY; REPRODUCIBILITY;

ARTIFICIAL INTELLIGENCE; COMPUTATIONAL BIOLOGY; P-GLYCOPROTEIN; REPRODUCIBILITY OF RESULTS;

EID: 79959742759     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci2001583     Document Type: Article

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