Recipe for uncovering predictive genes using support vector machines based on model population analysis

IEEE/ACM Transactions on Computational Biology and Bioinformatics

Volumn 8, Issue 6, 2011, Pages 1633-1641

  Li, Hong Dong ^a   Liang, Yi Zeng ^a   Xu, Qing Song ^a   Cao, Dong Sheng ^a   Tan, Bin Bin ^a   Deng, Bai Chuan ^a   Lin, Chen Chen ^a  

^a CENTRAL SOUTH UNIVERSITY   (China)

Author keywords

cancer classification; Informative gene selection; margin; Model population analysis; support vector machines

Indexed keywords

CANCER CLASSIFICATION; CANCER PREDICTION; CLASSIFICATION ACCURACY; GENE SELECTION; GENERALIZATION PERFORMANCE; GNU GENERAL PUBLIC LICENSE; HIGH-DIMENSIONAL; INFLUENCE ANALYSIS; INFORMATIVE GENE SELECTION; INFORMATIVE GENES; MANN-WHITNEY U TEST; MARGIN; MICROARRAY DATA; MICROARRAY DATA SETS; NON-PARAMETRIC TEST; POPULATION ANALYSIS; ROBUST METHODS; SOURCE CODES; SUPPORT VECTOR; SVM MODEL; T-TESTS; TUMOR CLASSIFICATION;

CLASSIFICATION (OF INFORMATION); DISEASES; FEATURE EXTRACTION; GENES; MICROARRAYS; POPULATION STATISTICS; STATISTICAL TESTS; VECTORS;

SUPPORT VECTOR MACHINES;

ARTICLE; DNA MICROARRAY; GENE EXPRESSION PROFILING; GENETIC DATABASE; HUMAN; METHODOLOGY; POPULATION GENETICS; SUPPORT VECTOR MACHINE;

DATABASES, GENETIC; GENE EXPRESSION PROFILING; GENETICS, POPULATION; HUMANS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; SUPPORT VECTOR MACHINES;

EID: 80052889367     PISSN: 15455963     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCBB.2011.36     Document Type: Article

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