A regression tree-based Gibbs sampler to learn the regulation programs in a transcription regulatory module network

2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2010

Volumn , Issue , 2010, Pages 126-133

  Qi, Jianlong ^a   Michoel, Tom ^b   Butler, Gregory ^a  

^a Dept of Electrical and Computer Engineering   (Canada)

^b GHENT UNIVERSITY   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN; BIOLOGICAL DATA; CONDITIONAL PROBABILITY DISTRIBUTIONS; GENE EXPRESSION DATA; GIBBS SAMPLERS; GIBBS SAMPLING; LARGE DATASETS; MODEL UNCERTAINTIES; MODULE NETWORKS; OVERFITTING; REGRESSION TREES; REGULATORY NETWORK; SEARCH ALGORITHMS; SEARCH SPACES; SYNTHETIC DATA; TREE OPERATIONS;

ARTIFICIAL INTELLIGENCE; BAYESIAN NETWORKS; BIOINFORMATICS; INFERENCE ENGINES; LAWS AND LEGISLATION; LEARNING ALGORITHMS; PROBABILITY DISTRIBUTIONS; REGRESSION ANALYSIS; SAMPLING; TRANSCRIPTION; UNCERTAINTY ANALYSIS;

TREES (MATHEMATICS);

EID: 77955593676     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CIBCB.2010.5510433     Document Type: Conference Paper

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