BayesMD: Flexible biological modeling for motif discovery

Journal of Computational Biology

Volumn 15, Issue 10, 2008, Pages 1347-1363

  Tang, Man Hung Eric ^a   Krogh, Anders ^a   Winther, Ole ^a,b  

^a UNIVERSITY OF COPENHAGEN   (Denmark)

^b TECHNICAL UNIVERSITY OF DENMARK   (Denmark)

Author keywords

Computational molecular biology; Gene expression; Machine learning; Markov chains; Monte Carlo likelihood; Recognition of genes and regulatory elements; Sequence analysis; Stochastic processes

Indexed keywords

NUCLEOTIDE; TRANSCRIPTION FACTOR;

ARTICLE; BAYES THEOREM; BINDING SITE; DATA BASE; GENE EXPRESSION; MACHINE LEARNING; MATHEMATICAL COMPUTING; MOLECULAR BIOLOGY; MONTE CARLO METHOD; NUCLEOSOME; PRIORITY JOURNAL; PROBABILITY; SAMPLING; SEQUENCE ANALYSIS;

ALGORITHMS; AMINO ACID MOTIFS; BASE SEQUENCE; BAYES THEOREM; MODELS, GENETIC; MOLECULAR SEQUENCE DATA; ROC CURVE; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS, DNA; SOFTWARE;

EID: 57149113149     PISSN: 10665277     EISSN: None     Source Type: Journal    
DOI: 10.1089/cmb.2007.0176     Document Type: Article

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