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Article: Detection of generic spaced motifs using submotif pattern mining
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TitleDetection of generic spaced motifs using submotif pattern mining
 
AuthorsWijaya, E2 4
Rajaraman, K2
Yiu, SM1
Sung, WK4 3
 
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
2013 Impact Factor: 4.621
 
DOIhttp://dx.doi.org/10.1093/bioinformatics/btm118
 
ISI Accession Number IDWOS:000248271700006
 
ReferencesReferences in Scopus
 
DC FieldValue
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
2013 Impact Factor: 4.621
 
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
 
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Author Affiliations
  1. The University of Hong Kong
  2. Institute for Infocomm Research, A-Star, Singapore
  3. Genome Institute of Singapore
  4. National University of Singapore