In silico identification of human pregnane X receptor activators from molecular descriptors by machine learning approaches

Chemometrics and Intelligent Laboratory Systems

Volumn 118, Issue , 2012, Pages 271-279

  Rao, Hanbing ^a   Wang, Yanying ^a   Zeng, Xianyin ^a   Wang, Xianxiang ^a   Liu, Yong ^a   Yin, Jiajian ^a   He, Hua ^a   Zhu, Feng ^b   Li, Zerong ^c  

^a SICHUAN AGRICULTURAL UNIVERSITY   (China)

^b NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^c SICHUAN UNIVERSITY   (China)

Author keywords

Applicability domain; HPXR; Machine learning approaches

Indexed keywords

AGENTS INTERACTING WITH TRANSMITTER, HORMONE OR DRUG RECEPTORS; HUMAN PREGNANE X RECEPTOR ACTIVATOR; UNCLASSIFIED DRUG;

ACCURACY; ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; COMPUTATIONAL MODEL; COMPUTER MODEL; CONTROLLED STUDY; FEATURE SELECTION METHOD; K NEAREST NEIGHBOR; MACHINE LEARNING; MATHEMATICAL MODEL; MONTE CARLO METHOD; PREDICTION; PRIORITY JOURNAL; SUPPORT VECTOR MACHINE;

EID: 84868212471     PISSN: 01697439     EISSN: 18733239     Source Type: Journal    
DOI: 10.1016/j.chemolab.2012.05.012     Document Type: Article

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