An integrated feature selection and classification method to select minimum number of variables on the case study of gene expression data

Journal of Bioinformatics and Computational Biology

Volumn 3, Issue 5, 2005, Pages 1107-1136

  Goh, Liang ^a   Kasabov, Nikola ^a  

^a AUCKLAND UNIVERSITY OF TECHNOLOGY   (New Zealand)

Author keywords

Cancer; Evolving connectionist systems; Feature selection

Indexed keywords

ACCURACY; ARTICLE; BIOINFORMATICS; BREAST CANCER; COMPARATIVE STUDY; COMPUTER MODEL; CORRELATION COEFFICIENT; DATA ANALYSIS; EVOLUTIONARY ADAPTATION; EXPERT SYSTEM; GENE EXPRESSION PROFILING; GENETIC ALGORITHM; GENETIC ANALYSIS; GENETIC DATABASE; INFORMATION PROCESSING; INFORMATION RETRIEVAL; LEUKEMIA; LUNG CANCER; LYMPHOMA; MARKER GENE; MATHEMATICAL COMPUTING; PROCESS OPTIMIZATION; SIGNAL NOISE RATIO; VALIDATION PROCESS;

ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; DIAGNOSIS, COMPUTER-ASSISTED; GENE EXPRESSION PROFILING; HUMANS; NEOPLASM PROTEINS; NEOPLASMS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SYSTEMS INTEGRATION; TUMOR MARKERS, BIOLOGICAL;

EID: 28044455863     PISSN: 02197200     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0219720005001533     Document Type: Article

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