Strategies for identifying statistically significant dense regions in microarray data

IEEE/ACM Transactions on Computational Biology and Bioinformatics

Volumn 4, Issue 3, 2007, Pages 415-428

  Yip, Andy M ^a   Ng, Michael K ^b   Wu, Edmond H ^c   Chan, Tony F ^d  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^b HONG KONG BAPTIST UNIVERSITY   (Hong Kong)

^c UNIVERSITY OF HONG KONG   (Hong Kong)

^d UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Bicluster; Categorical data; Clustering; Coexpressed genes; Dense region; Gene expression; Microarray

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; DIGITAL LIBRARIES; GENE EXPRESSION;

CATEGORICAL DATA; COEXPRESSED GENES; DENSE REGION; SEARCHING ALGORITHMS;

MICROARRAYS;

ALGORITHM; ARTICLE; CLUSTER ANALYSIS; DATA BASE; DNA MICROARRAY; GENE EXPRESSION PROFILING; GENETICS; INFORMATION RETRIEVAL; METHODOLOGY; MULTIGENE FAMILY; PROTEIN DATABASE; STATISTICAL ANALYSIS;

ALGORITHMS; CLUSTER ANALYSIS; DATA INTERPRETATION, STATISTICAL; DATABASE MANAGEMENT SYSTEMS; DATABASES, PROTEIN; GENE EXPRESSION PROFILING; INFORMATION STORAGE AND RETRIEVAL; MULTIGENE FAMILY; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS;

EID: 34547973950     PISSN: 15455963     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCBB.2007.1022     Document Type: Article

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