Improving accuracy for cancer classification with a new algorithm for genes selection

BMC Bioinformatics

Volumn 13, Issue 1, 2012, Pages

  Zhang, Hongyan ^a,b   Wang, Haiyan ^c   Dai, Zhijun ^a,b   Chen, Ming shun ^c   Yuan, Zheming ^a,b  

^a Hunan Provincial Key Laboratory of Crop Germplasm Innovation and Utilization   (China)

^b HUNAN AGRICULTURAL UNIVERSITY   (China)

^c KANSAS STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BINARY MATRIX; CANCER CLASSIFICATION; CANCER TISSUES; CLASSIFICATION ACCURACY; COMPUTATIONALLY EFFICIENT; FEATURE SPACE; GENE EXPRESSION DATA; GENE EXPRESSION DATASETS; GENE INTERACTIONS; GENE SELECTION; HUMAN CANCER; INFORMATIVE GENES; JOINT EFFECT; LEAVE-ONE-OUT; MULTIPLE CLASSIFIERS; OVER FITTING PROBLEM; SEARCH SCHEME; SEARCH SPACES; WRAPPER METHODS;

ALGORITHMS; DISEASES; GENE EXPRESSION; SUPPORT VECTOR MACHINES; TISSUE;

CLASSIFICATION (OF INFORMATION);

ALGORITHM; ARTICLE; BIOLOGY; CLASSIFICATION; GENE EXPRESSION; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENETICS; HUMAN; METHODOLOGY; NEOPLASM; SUPPORT VECTOR MACHINE; TUMOR GENE;

ALGORITHMS; COMPUTATIONAL BIOLOGY; GENE EXPRESSION; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION, NEOPLASTIC; GENES, NEOPLASM; HUMANS; NEOPLASMS; SUPPORT VECTOR MACHINES;

MLCS; MLOWN;

EID: 84868640681     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-13-298     Document Type: Article

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