Article: Detection of generic spaced motifs using submotif pattern mining

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TitleDetection of generic spaced motifs using submotif pattern mining
AuthorsWijaya, E1 4
Rajaraman, K1
Yiu, SM2
Sung, WK3 4
Issue Date2007
PublisherOxford University Press. The Journal's web site is located at http://bioinformatics.oxfordjournals.org/
CitationBioinformatics, 2007, v. 23 n. 12, p. 1476-1485 [How to Cite?]
DOI: http://dx.doi.org/10.1093/bioinformatics/btm118
AbstractMotivation: Identification of motifs is one of the critical stages in studying the regulatory interactions of genes. Motifs can have complicated patterns. In particular, spaced motifs, an important class of motifs, consist of several short segments separated by spacers of different lengths. Locating spaced motifs is not trivial. Existing motif-finding algorithms are either designed for monad motifs (short contiguous patterns with some mismatches) or have assumptions on the spacer lengths or can only handle at most two segments. An effective motif finder for generic spaced motifs is highly desirable. Results: This article proposes a novel approach for identifying spaced motifs with any number of spacers of different lengths. We introduce the notion of submotifs to capture the segments in the spaced motif and formulate the motif-finding problem as a frequent submotif mining problem. We provide an algorithm called SPACE to solve the problem. Based on experiments on real biological datasets, synthetic datasets and the motif assessment benchmarks by Tompa et al., we show that our algorithm performs better than existing tools for spaced motifs with improvements in both sensitivity and specificity and for monads, SPACE performs as good as other tools. © The Author 2007. Published by Oxford University Press. All rights reserved.
ISSN1367-4803
2011 Impact Factor: 5.468
2011 SCImago Journal Rankings: 1.118
DOIhttp://dx.doi.org/10.1093/bioinformatics/btm118
ReferencesReferences in Scopus
DC Field
Value
dc.contributor.authorWijaya, E
dc.contributor.authorRajaraman, K
dc.contributor.authorYiu, SM
dc.contributor.authorSung, WK
dc.date.accessioned2010-09-06T09:50:45Z
dc.date.available2010-09-06T09:50:45Z
dc.date.issued2007
dc.description.abstractMotivation: Identification of motifs is one of the critical stages in studying the regulatory interactions of genes. Motifs can have complicated patterns. In particular, spaced motifs, an important class of motifs, consist of several short segments separated by spacers of different lengths. Locating spaced motifs is not trivial. Existing motif-finding algorithms are either designed for monad motifs (short contiguous patterns with some mismatches) or have assumptions on the spacer lengths or can only handle at most two segments. An effective motif finder for generic spaced motifs is highly desirable. Results: This article proposes a novel approach for identifying spaced motifs with any number of spacers of different lengths. We introduce the notion of submotifs to capture the segments in the spaced motif and formulate the motif-finding problem as a frequent submotif mining problem. We provide an algorithm called SPACE to solve the problem. Based on experiments on real biological datasets, synthetic datasets and the motif assessment benchmarks by Tompa et al., we show that our algorithm performs better than existing tools for spaced motifs with improvements in both sensitivity and specificity and for monads, SPACE performs as good as other tools. © The Author 2007. Published by Oxford University Press. All rights reserved.
dc.description.naturelink_to_OA_fulltext
dc.identifier.citationBioinformatics, 2007, v. 23 n. 12, p. 1476-1485 [How to Cite?]
DOI: http://dx.doi.org/10.1093/bioinformatics/btm118
dc.identifier.citeulike1365971
dc.identifier.doihttp://dx.doi.org/10.1093/bioinformatics/btm118
dc.identifier.epage1485
dc.identifier.hkuros161322
dc.identifier.isiWOS:000248271700006
dc.identifier.issn1367-4803
2011 Impact Factor: 5.468
2011 SCImago Journal Rankings: 1.118
dc.identifier.issue12
dc.identifier.openurl
dc.identifier.pmid17483509
dc.identifier.scopuseid_2-s2.0-34547840183
dc.identifier.spage1476
dc.identifier.urihttp://hdl.handle.net/10722/88970
dc.identifier.volume23
dc.languageeng
dc.publisherOxford University Press. The Journal's web site is located at http://bioinformatics.oxfordjournals.org/
dc.publisher.placeUnited Kingdom
dc.relation.ispartofBioinformatics
dc.relation.referencesReferences in Scopus
dc.subject.meshAmino Acid Motifs
dc.subject.meshComputational Biology - methods
dc.subject.meshPattern Recognition, Automated
dc.subject.meshProtein Structure, Tertiary
dc.subject.meshTranscription Factors/genetics
dc.titleDetection of generic spaced motifs using submotif pattern mining
dc.typeArticle
Author Affiliations
  1. Institute for Infocomm Research, A-Star, Singapore
  2. The University of Hong Kong
  3. Genome Institute of Singapore
  4. National University of Singapore