The effect of prior assumptions over the weights in BayesPI with application to study protein-DNA interactions from ChIP-based high-throughput data

BMC Bioinformatics

Volumn 11, Issue , 2010, Pages

  Wang, Junbai ^a  

^a OSLO UNIVERSITY HOSPITAL   (Norway)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION METHODS; BAYESIAN HIERARCHICAL MODEL; COMPUTATIONAL IMPLEMENTATIONS; COMPUTATIONAL SPEED; EFFICIENT LEARNING; HIGH-THROUGHPUT DATA; PROTEIN-DNA INTERACTIONS; QUALITY OF PREDICTIONS;

APPROXIMATION THEORY; BINDING ENERGY; BIOCHEMISTRY; LAPLACE TRANSFORMS; MONTE CARLO METHODS; PROBABILITY DISTRIBUTIONS;

HIERARCHICAL SYSTEMS;

DNA; DNA BINDING PROTEIN;

ALGORITHM; ARTICLE; BAYES THEOREM; CHROMATIN IMMUNOPRECIPITATION; DNA MICROARRAY; DNA SEQUENCE; METABOLISM; MONTE CARLO METHOD;

ALGORITHMS; BAYES THEOREM; CHROMATIN IMMUNOPRECIPITATION; DNA; DNA-BINDING PROTEINS; MONTE CARLO METHOD; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; SEQUENCE ANALYSIS, DNA;

EID: 77955120332     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-11-412     Document Type: Article

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