A novel parametric approach to mine gene regulatory relationship from microarray datasets

BMC Bioinformatics

Volumn 11, Issue SUPPL. 11, 2010, Pages

  Liu, Wanlin ^a   Li, Dong ^a   Liu, Qijun ^a,b   Zhu, Yunping ^a   He, Fuchu ^a  

^a BEIJING INSTITUTE OF RADIATION MEDICINE   (China)

^b NATIONAL UNIVERSITY OF DEFENSE TECHNOLOGY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

BASIC CHARACTERISTICS; GENE EXPRESSION LEVELS; GENE REGULATORY NETWORKS; GENE REGULATORY RELATIONSHIPS; MICROARRAY DATA SETS; MICROARRAY EXPRESSIONS; MODELS AND ALGORITHMS; REGULATORY RELATIONSHIPS;

ALGORITHMS; BAYESIAN NETWORKS; DATA REDUCTION; GENE EXPRESSION REGULATION;

GENE EXPRESSION;

TRANSCRIPTION FACTOR;

ALGORITHM; ARTICLE; BAYES THEOREM; DATA MINING; DNA MICROARRAY; GENE EXPRESSION; GENE EXPRESSION PROFILING; GENE REGULATORY NETWORK; METABOLISM; METHODOLOGY; STATISTICAL MODEL;

ALGORITHMS; BAYES THEOREM; DATA MINING; GENE EXPRESSION; GENE EXPRESSION PROFILING; GENE REGULATORY NETWORKS; LIKELIHOOD FUNCTIONS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; TRANSCRIPTION FACTORS;

EID: 78650819884     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-11-S11-S15     Document Type: Article

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