| Detection of generic spaced motifs using submotif pattern mining. | |
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MedLine Citation:
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PMID: 17483509 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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MOTIVATION: 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. AVAILABILITY: The source code is available upon request from the authors. |
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Authors:
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Edward Wijaya; Kanagasabai Rajaraman; Siu-Ming Yiu; Wing-Kin Sung |
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Publication Detail:
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Type: Comparative Study; Journal Article; Research Support, Non-U.S. Gov't Date: 2007-05-05 |
Journal Detail:
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Title: Bioinformatics (Oxford, England) Volume: 23 ISSN: 1367-4811 ISO Abbreviation: Bioinformatics Publication Date: 2007 Jun |
Date Detail:
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Created Date: 2007-07-09 Completed Date: 2007-08-23 Revised Date: 2009-11-04 |
Medline Journal Info:
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Nlm Unique ID: 9808944 Medline TA: Bioinformatics Country: England |
Other Details:
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Languages: eng Pagination: 1476-85 Citation Subset: IM |
Affiliation:
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Institute for Infocomm Research, Singapore. |
Export Citation:
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APA/MLA Format Download EndNote Download BibTex |
| MeSH Terms | |
Descriptor/Qualifier:
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Algorithms Amino Acid Motifs* Base Sequence Binding Sites Computational Biology / methods* Models, Statistical Pattern Recognition, Automated* Protein Binding Protein Structure, Tertiary Sequence Alignment Sequence Analysis, DNA Transcription Factors / genetics |
| Chemical | |
Reg. No./Substance:
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0/Transcription Factors |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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