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Article: Finding exact optimal motifs in matrix representation by partitioning

TitleFinding exact optimal motifs in matrix representation by partitioning
Authors
Issue Date2005
PublisherOxford University Press. The Journal's web site is located at http://bioinformatics.oxfordjournals.org/
Citation
Bioinformatics, 2005, v. 21 SUPPL. 2, p. ii86-ii92 How to Cite?
AbstractMotivation: Finding common patterns, or motifs, in the promoter regions of co-expressed genes is an important problem in bioinformatics. A common representation of the motif is by probability matrix or PSSM (position specific scoring matrix). However, even for a motif of length six or seven, there is no algorithm that can guarantee finding the exact optimal matrix from an infinite number of possible matrices. Results: T his paper introduces the first algorithm, called EOMM, for finding the exact optimal matrix-represented motif, or simply optimal motif. Based on branch-and-bound searching by partitioning the solution space recursively, EOMM can find the optimal motif of size up to eight or nine, and a motif of larger size with any desired accuracy on the principle that the smaller the error bound, the longer the running time. Experiments show that for some real and simulated data sets, EOMM finds the motif despite very weak signals when existing software, such as MEME and MITRA-PSSM, fails to do so. © The Author 2005. Published by Oxford University Press. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/53599
ISSN
2023 Impact Factor: 4.4
2023 SCImago Journal Rankings: 2.574
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorLeung, HCMen_HK
dc.contributor.authorChin, FYLen_HK
dc.date.accessioned2009-04-03T07:24:17Z-
dc.date.available2009-04-03T07:24:17Z-
dc.date.issued2005en_HK
dc.identifier.citationBioinformatics, 2005, v. 21 SUPPL. 2, p. ii86-ii92en_HK
dc.identifier.issn1367-4803en_HK
dc.identifier.urihttp://hdl.handle.net/10722/53599-
dc.description.abstractMotivation: Finding common patterns, or motifs, in the promoter regions of co-expressed genes is an important problem in bioinformatics. A common representation of the motif is by probability matrix or PSSM (position specific scoring matrix). However, even for a motif of length six or seven, there is no algorithm that can guarantee finding the exact optimal matrix from an infinite number of possible matrices. Results: T his paper introduces the first algorithm, called EOMM, for finding the exact optimal matrix-represented motif, or simply optimal motif. Based on branch-and-bound searching by partitioning the solution space recursively, EOMM can find the optimal motif of size up to eight or nine, and a motif of larger size with any desired accuracy on the principle that the smaller the error bound, the longer the running time. Experiments show that for some real and simulated data sets, EOMM finds the motif despite very weak signals when existing software, such as MEME and MITRA-PSSM, fails to do so. © The Author 2005. Published by Oxford University Press. All rights reserved.en_HK
dc.languageengen_HK
dc.publisherOxford University Press. The Journal's web site is located at http://bioinformatics.oxfordjournals.org/en_HK
dc.relation.ispartofBioinformaticsen_HK
dc.rightsBioinformatics. Copyright © Oxford University Press.en_HK
dc.rightsThis is a pre-copy-editing, author-produced PDF of an article accepted for publication in Bioinformatics, following peer review. The definitive publisher-authenticated version is available online at: http://bioinformatics.oxfordjournals.org/en_HK
dc.subject.meshAlgorithmsen_HK
dc.subject.meshMultigene Family - geneticsen_HK
dc.subject.meshMolecular Sequence Dataen_HK
dc.subject.meshBase Sequenceen_HK
dc.subject.meshProteins - geneticsen_HK
dc.titleFinding exact optimal motifs in matrix representation by partitioningen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1367-4803&volume=21&issue=Supp 2&spage=ii86&epage=ii92&date=2005&atitle=Finding+exact+optimal+motifs+in+matrix+representation+by+partitioningen_HK
dc.identifier.emailLeung, HCM:cmleung2@cs.hku.hken_HK
dc.identifier.emailChin, FYL:chin@cs.hku.hken_HK
dc.identifier.authorityLeung, HCM=rp00144en_HK
dc.identifier.authorityChin, FYL=rp00105en_HK
dc.description.naturepostprinten_HK
dc.identifier.doi10.1093/bioinformatics/bti1115en_HK
dc.identifier.pmid16204132-
dc.identifier.scopuseid_2-s2.0-27544437350en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-27544437350&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume21en_HK
dc.identifier.issueSUPPL. 2en_HK
dc.identifier.spageii86en_HK
dc.identifier.epageii92en_HK
dc.identifier.isiWOS:000232421000017-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridLeung, HCM=35233742700en_HK
dc.identifier.scopusauthoridChin, FYL=7005101915en_HK
dc.identifier.citeulike881858-
dc.identifier.issnl1367-4803-

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