Exploring the within- and between-class correlation distributions for tumor classification

Proceedings of the National Academy of Sciences of the United States of America

Volumn 107, Issue 15, 2010, Pages 6737-6742

  Wei, Xuelian ^a   Li, Ker Chau ^a,b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b INSTITUTE OF STATISTICAL SCIENCE   (Taiwan)

Author keywords

Cancer research; Gene expression

Indexed keywords

ARTICLE; BAYES THEOREM; CANCER RESEARCH; CORRELATION ANALYSIS; DECISION TREE; GENE EXPRESSION; MACHINE LEARNING; PRIORITY JOURNAL; STATISTICAL ANALYSIS; SUPPORT VECTOR MACHINE; TUMOR CLASSIFICATION;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; CLUSTER ANALYSIS; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION, NEOPLASTIC; HUMANS; MEDICAL ONCOLOGY; MODELS, STATISTICAL; MULTIVARIATE ANALYSIS; NEOPLASMS; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS;

EID: 77951067219     PISSN: 00278424     EISSN: 10916490     Source Type: Journal    
DOI: 10.1073/pnas.0910140107     Document Type: Article

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