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Article: Discovering motifs with transcription factor domain knowledge.

TitleDiscovering motifs with transcription factor domain knowledge.
Authors
Issue Date2007
Citation
Pacific Symposium On Biocomputing. Pacific Symposium On Biocomputing, 2007, p. 472-483 How to Cite?
AbstractWe introduce a new motif-discovery algorithm, DIMDom, which exploits two additional kinds of information not commonly exploited: (a) the characteristic pattern of binding site classes, where class is determined based on biological information about transcription factor domains and (b) posterior probabilities of these classes. We compared the performance of DIMDom with MEME on all the transcription factors of Drosophila with at least one known binding site in the TRANSFAC database and found that DOMDom outperformed MEME with 2.5 times the number of successes and 1.5 times in the accuracy in finding binding sties and motifs.
Persistent Identifierhttp://hdl.handle.net/10722/152382
ISSN

 

DC FieldValueLanguage
dc.contributor.authorLeung, HCen_US
dc.contributor.authorChin, FYen_US
dc.contributor.authorChan, BMen_US
dc.date.accessioned2012-06-26T06:37:48Z-
dc.date.available2012-06-26T06:37:48Z-
dc.date.issued2007en_US
dc.identifier.citationPacific Symposium On Biocomputing. Pacific Symposium On Biocomputing, 2007, p. 472-483en_US
dc.identifier.issn1793-5091en_US
dc.identifier.urihttp://hdl.handle.net/10722/152382-
dc.description.abstractWe introduce a new motif-discovery algorithm, DIMDom, which exploits two additional kinds of information not commonly exploited: (a) the characteristic pattern of binding site classes, where class is determined based on biological information about transcription factor domains and (b) posterior probabilities of these classes. We compared the performance of DIMDom with MEME on all the transcription factors of Drosophila with at least one known binding site in the TRANSFAC database and found that DOMDom outperformed MEME with 2.5 times the number of successes and 1.5 times in the accuracy in finding binding sties and motifs.en_US
dc.languageengen_US
dc.relation.ispartofPacific Symposium on Biocomputing. Pacific Symposium on Biocomputingen_US
dc.subject.meshAlgorithmsen_US
dc.subject.meshAnimalsen_US
dc.subject.meshBayes Theoremen_US
dc.subject.meshBinding Sites - Geneticsen_US
dc.subject.meshComputational Biologyen_US
dc.subject.meshDna - Genetics - Metabolismen_US
dc.subject.meshDrosophila - Genetics - Metabolismen_US
dc.subject.meshModels, Biologicalen_US
dc.subject.meshPromoter Regions, Geneticen_US
dc.subject.meshProtein Structure, Tertiaryen_US
dc.subject.meshTranscription Factors - Chemistry - Metabolismen_US
dc.titleDiscovering motifs with transcription factor domain knowledge.en_US
dc.typeArticleen_US
dc.identifier.emailLeung, HC:cmleung2@cs.hku.hken_US
dc.identifier.emailChin, FY:chin@cs.hku.hken_US
dc.identifier.authorityLeung, HC=rp00144en_US
dc.identifier.authorityChin, FY=rp00105en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.pmid17990511-
dc.identifier.scopuseid_2-s2.0-38449121252en_US
dc.identifier.spage472en_US
dc.identifier.epage483en_US
dc.identifier.scopusauthoridLeung, HC=35233742700en_US
dc.identifier.scopusauthoridChin, FY=7005101915en_US
dc.identifier.scopusauthoridChan, BM=23472088900en_US

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