Quantitative utilization of prior biological knowledge in the Bayesian network modeling of gene expression data

BMC Bioinformatics

Volumn 12, Issue , 2011, Pages

  Gao, Shouguo ^a,b   Wang, Xujing ^a,b  

^a UNIVERSITY OF ALABAMA AT BIRMINGHAM   (United States)

^b UNIVERSITY OF ALABAMA AT BIRMINGHAM   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN NETWORK MODELS; GENE ONTOLOGY ANNOTATIONS; GENETIC REGULATORY NETWORKS; INCORPORATING PRIOR KNOWLEDGE; INTEGRATING MULTIPLE SOURCES; MARKOV CHAIN MONTE CARLO SAMPLINGS; QUANTITATIVE INFORMATION; TRANSCRIPTION REGULATIONS;

ALGORITHMS; BAYESIAN NETWORKS; GENES; ITERATIVE METHODS; MONTE CARLO METHODS; TRANSCRIPTION;

COMPUTER SIMULATION;

SACCHAROMYCES CEREVISIAE PROTEIN;

ALGORITHM; ANIMAL; ARTICLE; BAYES THEOREM; BIOLOGICAL MODEL; BIOLOGY; CYTOLOGY; GENE EXPRESSION PROFILING; GENETICS; MEDLINE; METABOLISM; METHODOLOGY; MOUSE; PANCREAS; PROBABILITY; SACCHAROMYCES CEREVISIAE;

ALGORITHMS; ANIMALS; BAYES THEOREM; COMPUTATIONAL BIOLOGY; GENE EXPRESSION PROFILING; MARKOV CHAINS; MICE; MODELS, GENETIC; PANCREAS; PROBABILITY; PUBMED; SACCHAROMYCES CEREVISIAE; SACCHAROMYCES CEREVISIAE PROTEINS;

EID: 80052176477     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-12-359     Document Type: Article

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