In silico toxicity prediction of chemicals from EPA toxicity database by kernel fusion-based support vector machines

Chemometrics and Intelligent Laboratory Systems

Volumn 146, Issue , 2015, Pages 494-502

  Cao, Dong Sheng ^a   Dong, Jie ^a   Wang, Ning Ning ^a   Wen, Ming ^a   Deng, Bai Chuan ^a   Zeng, Wen Bin ^a   Xu, Qing Song ^a   Liang, Yi Zeng ^a   Lu, Ai Ping ^b   Chen, Alex F ^a  

^a CENTRAL SOUTH UNIVERSITY   (China)

^b HONG KONG BAPTIST UNIVERSITY   (Hong Kong)

Author keywords

Data fusion; Kernel fusion; Kernel methods; Support vector machine; Toxicity prediction

Indexed keywords

ARTICLE; BIOASSAY; CHEMICAL ANALYSIS; CLUSTER ANALYSIS; CORRELATION COEFFICIENT; DATA BASE; DISTRIBUTED STRUCTURE SEARCHABLE TOXICITY DATABASE; KERNEL METHOD; MACHINE LEARNING; PREDICTION; PRIORITY JOURNAL; PROBABILITY; QUANTITATIVE ANALYSIS; RECEIVER OPERATING CHARACTERISTIC; SUPPORT VECTOR MACHINE; TOXICITY TESTING;

EID: 84937929751     PISSN: 01697439     EISSN: 18733239     Source Type: Journal    
DOI: 10.1016/j.chemolab.2015.07.009     Document Type: Article

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