Class discovery from gene expression data based on perturbation and cluster ensemble

IEEE Transactions on Nanobioscience

Volumn 8, Issue 2, 2009, Pages 147-160

  Yu, Zhiwen ^a,b   Wong, Hau San ^b  

^a SOUTH CHINA UNIVERSITY OF TECHNOLOGY   (China)

^b CITY UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Class discover; Cluster ensemble; Cluster validity index; Microarray; Perturbation

Indexed keywords

CANCER DIAGNOSIS; CLASS DISCOVER; CLUSTER ENSEMBLE; CLUSTER ENSEMBLES; CLUSTER VALIDITY; CLUSTER VALIDITY INDEX; CLUSTER VALIDITY INDICES; DATA SETS; GENE EXPRESSION DATA; MICROARRAY DATA; NEURAL GAS; PERTURBATION; SYNTHETIC DATASETS;

BIOACTIVITY; CLUSTERING ALGORITHMS; FUZZY CLUSTERING; GENE EXPRESSION;

PERTURBATION TECHNIQUES;

ALGORITHM; ARTICLE; CLUSTER ANALYSIS; DATA BASE; GENE EXPRESSION; MICROARRAY ANALYSIS; VALIDITY;

ALGORITHMS; CLUSTER ANALYSIS; GENE EXPRESSION PROFILING; HUMANS; NEOPLASM PROTEINS; NEOPLASMS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PATTERN RECOGNITION, AUTOMATED; SIGNAL TRANSDUCTION; TUMOR MARKERS, BIOLOGICAL;

EID: 68949086993     PISSN: 15361241     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNB.2009.2023321     Document Type: Article

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