PMID:14962923: Difference between revisions

Latest revision as of 04:23, 15 September 2013

Citation	Jensen, ST and Liu, JS (2004) BioOptimizer: a Bayesian scoring function approach to motif discovery. Bioinformatics 20:1557-64
Abstract	Transcription factors (TFs) bind directly to short segments on the genome, often within hundreds to thousands of base pairs upstream of gene transcription start sites, to regulate gene expression. The experimental determination of TFs binding sites is expensive and time-consuming. Many motif-finding programs have been developed, but no program is clearly superior in all situations. Practitioners often find it difficult to judge which of the motifs predicted by these algorithms are more likely to be biologically relevant.
Links	PubMed Online version:10.1093/bioinformatics/bth127
Keywords	Algorithms; Amino Acid Motifs; Bayes Theorem; Binding Sites; DNA/chemistry; Protein Binding; Sequence Alignment/methods; Sequence Analysis, DNA/methods; Software; Transcription Factors/chemistry
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-'''No author listed'''  (2004) BioOptimizer: a Bayesian scoring function approach to motif discovery. ''Bioinformatics'' '''20''':1557-64
+'''Jensen, ST and Liu, JS'''  (2004) BioOptimizer: a Bayesian scoring function approach to motif discovery. ''Bioinformatics'' '''20''':1557-64
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