Improving prediction accuracy of drug activities by utilising unlabelled instances with feature selection

International Journal of Computational Biology and Drug Design

Volumn 1, Issue 1, 2008, Pages 1-13

  Li, Guo Zheng ^a   Yang, Jack Y ^b   Lu, Wen Cong ^a   Li, Dan ^a   Qu Yang, Mary ^c  

^a SHANGHAI UNIVERSITY   (China)

^b HARVARD MEDICAL SCHOOL   (United States)

^c NATIONAL HUMAN GENOME RESEARCH INSTITUTE   (United States)

Author keywords

Co Training; feature selection; K Nearest Neighbor; KNN; QSAR; Semi Supervised Learning; SSL

Indexed keywords

ARTICLE; ARTIFICIAL INTELLIGENCE; BIOLOGICAL MODEL; BIOLOGY; COMPUTER SIMULATION; DRUG DESIGN; FACTUAL DATABASE; MUTAGEN TESTING; QUANTITATIVE STRUCTURE ACTIVITY RELATION; STATISTICS;

ARTIFICIAL INTELLIGENCE; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; DATABASES, FACTUAL; DRUG DESIGN; MODELS, BIOLOGICAL; MUTAGENICITY TESTS; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP;

EID: 77449116010     PISSN: 17560756     EISSN: 17560764     Source Type: Journal    
DOI: 10.1504/IJCBDD.2008.018706     Document Type: Article

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