PairMotif+: A Fast and Effective Algorithm for De Novo Motif Discovery in DNA sequences
Identifieur interne : 000A47 ( Ncbi/Merge ); précédent : 000A46; suivant : 000A48PairMotif+: A Fast and Effective Algorithm for De Novo Motif Discovery in DNA sequences
Auteurs : Qiang Yu ; Hongwei Huo ; Yipu Zhang ; Hongzhi Guo ; Haitao GuoSource :
- International Journal of Biological Sciences [ 1449-2288 ] ; 2013.
Descripteurs français
- KwdFr :
- MESH :
- génétique : Séquence nucléotidique.
- Algorithmes, Biologie informatique.
English descriptors
- KwdEn :
- MESH :
- genetics : Base Sequence.
- methods : Computational Biology.
- Algorithms.
Abstract
The planted (
Url:
DOI: 10.7150/ijbs.5786
PubMed: 23678291
PubMed Central: 3654438
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PMC:3654438Le document en format XML
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<front><div type="abstract" xml:lang="en"><p>The planted (<italic>l</italic>
, <italic>d</italic>
) motif search is one of the most widely studied problems in bioinformatics, which plays an important role in the identification of transcription factor binding sites in DNA sequences. However, it is still a challenging task to identify highly degenerate motifs, since current algorithms either output the exact results with a high computational cost or accomplish the computation in a short time but very often fall into a local optimum. In order to make a better trade-off between accuracy and efficiency, we propose a new pattern-driven algorithm, named PairMotif+. At first, some pairs of <italic>l</italic>
-mers are extracted from input sequences according to probabilistic analysis and statistical method so that one or more pairs of motif instances are included in them. Then an approximate strategy for refining pairs of <italic>l</italic>
-mers with high accuracy is adopted in order to avoid the verification of most candidate motifs. Experimental results on the simulated data show that PairMotif+ can solve various (<italic>l, d</italic>
) problems within an hour on a PC with 2.67 GHz processor, and has a better identification accuracy than the compared algorithms MEME, AlignACE and VINE. Also, the validity of the proposed algorithm is tested on multiple real data sets.</p>
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<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">PairMotif+: A Fast and Effective Algorithm for De Novo Motif Discovery in DNA sequences</title>
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<front><div type="abstract" xml:lang="en"><p>The planted (<italic>l</italic>
, <italic>d</italic>
) motif search is one of the most widely studied problems in bioinformatics, which plays an important role in the identification of transcription factor binding sites in DNA sequences. However, it is still a challenging task to identify highly degenerate motifs, since current algorithms either output the exact results with a high computational cost or accomplish the computation in a short time but very often fall into a local optimum. In order to make a better trade-off between accuracy and efficiency, we propose a new pattern-driven algorithm, named PairMotif+. At first, some pairs of <italic>l</italic>
-mers are extracted from input sequences according to probabilistic analysis and statistical method so that one or more pairs of motif instances are included in them. Then an approximate strategy for refining pairs of <italic>l</italic>
-mers with high accuracy is adopted in order to avoid the verification of most candidate motifs. Experimental results on the simulated data show that PairMotif+ can solve various (<italic>l, d</italic>
) problems within an hour on a PC with 2.67 GHz processor, and has a better identification accuracy than the compared algorithms MEME, AlignACE and VINE. Also, the validity of the proposed algorithm is tested on multiple real data sets.</p>
</div>
</front>
<back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Buhler, J" uniqKey="Buhler J">J Buhler</name>
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</author>
<author><name sortKey="Smith, Ad" uniqKey="Smith A">AD Smith</name>
</author>
<author><name sortKey="Wareham, Ht" uniqKey="Wareham H">HT Wareham</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Ho, Es" uniqKey="Ho E">ES Ho</name>
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<author><name sortKey="Gunderson, Si" uniqKey="Gunderson S">SI Gunderson</name>
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<author><name sortKey="Low, Myh" uniqKey="Low M">MYH Low</name>
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<pubmed><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">PairMotif+: a fast and effective algorithm for de novo motif discovery in DNA sequences.</title>
<author><name sortKey="Yu, Qiang" sort="Yu, Qiang" uniqKey="Yu Q" first="Qiang" last="Yu">Qiang Yu</name>
<affiliation wicri:level="1"><nlm:affiliation>School of Computer Science and Technology, Xidian University, Xi'an 710071, China.</nlm:affiliation>
<country xml:lang="fr">République populaire de Chine</country>
<wicri:regionArea>School of Computer Science and Technology, Xidian University, Xi'an 710071</wicri:regionArea>
<wicri:noRegion>Xi'an 710071</wicri:noRegion>
</affiliation>
</author>
<author><name sortKey="Huo, Hongwei" sort="Huo, Hongwei" uniqKey="Huo H" first="Hongwei" last="Huo">Hongwei Huo</name>
</author>
<author><name sortKey="Zhang, Yipu" sort="Zhang, Yipu" uniqKey="Zhang Y" first="Yipu" last="Zhang">Yipu Zhang</name>
</author>
<author><name sortKey="Guo, Hongzhi" sort="Guo, Hongzhi" uniqKey="Guo H" first="Hongzhi" last="Guo">Hongzhi Guo</name>
</author>
<author><name sortKey="Guo, Haitao" sort="Guo, Haitao" uniqKey="Guo H" first="Haitao" last="Guo">Haitao Guo</name>
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<date when="2013">2013</date>
<idno type="RBID">pubmed:23678291</idno>
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<idno type="doi">10.7150/ijbs.5786</idno>
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<sourceDesc><biblStruct><analytic><title xml:lang="en">PairMotif+: a fast and effective algorithm for de novo motif discovery in DNA sequences.</title>
<author><name sortKey="Yu, Qiang" sort="Yu, Qiang" uniqKey="Yu Q" first="Qiang" last="Yu">Qiang Yu</name>
<affiliation wicri:level="1"><nlm:affiliation>School of Computer Science and Technology, Xidian University, Xi'an 710071, China.</nlm:affiliation>
<country xml:lang="fr">République populaire de Chine</country>
<wicri:regionArea>School of Computer Science and Technology, Xidian University, Xi'an 710071</wicri:regionArea>
<wicri:noRegion>Xi'an 710071</wicri:noRegion>
</affiliation>
</author>
<author><name sortKey="Huo, Hongwei" sort="Huo, Hongwei" uniqKey="Huo H" first="Hongwei" last="Huo">Hongwei Huo</name>
</author>
<author><name sortKey="Zhang, Yipu" sort="Zhang, Yipu" uniqKey="Zhang Y" first="Yipu" last="Zhang">Yipu Zhang</name>
</author>
<author><name sortKey="Guo, Hongzhi" sort="Guo, Hongzhi" uniqKey="Guo H" first="Hongzhi" last="Guo">Hongzhi Guo</name>
</author>
<author><name sortKey="Guo, Haitao" sort="Guo, Haitao" uniqKey="Guo H" first="Haitao" last="Guo">Haitao Guo</name>
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<series><title level="j">International journal of biological sciences</title>
<idno type="eISSN">1449-2288</idno>
<imprint><date when="2013" type="published">2013</date>
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<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms</term>
<term>Base Sequence (genetics)</term>
<term>Computational Biology (methods)</term>
</keywords>
<keywords scheme="KwdFr" xml:lang="fr"><term>Algorithmes</term>
<term>Biologie informatique ()</term>
<term>Séquence nucléotidique (génétique)</term>
</keywords>
<keywords scheme="MESH" qualifier="genetics" xml:lang="en"><term>Base Sequence</term>
</keywords>
<keywords scheme="MESH" qualifier="génétique" xml:lang="fr"><term>Séquence nucléotidique</term>
</keywords>
<keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Computational Biology</term>
</keywords>
<keywords scheme="MESH" xml:lang="en"><term>Algorithms</term>
</keywords>
<keywords scheme="MESH" xml:lang="fr"><term>Algorithmes</term>
<term>Biologie informatique</term>
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<front><div type="abstract" xml:lang="en">The planted (l, d) motif search is one of the most widely studied problems in bioinformatics, which plays an important role in the identification of transcription factor binding sites in DNA sequences. However, it is still a challenging task to identify highly degenerate motifs, since current algorithms either output the exact results with a high computational cost or accomplish the computation in a short time but very often fall into a local optimum. In order to make a better trade-off between accuracy and efficiency, we propose a new pattern-driven algorithm, named PairMotif+. At first, some pairs of l-mers are extracted from input sequences according to probabilistic analysis and statistical method so that one or more pairs of motif instances are included in them. Then an approximate strategy for refining pairs of l-mers with high accuracy is adopted in order to avoid the verification of most candidate motifs. Experimental results on the simulated data show that PairMotif+ can solve various (l, d) problems within an hour on a PC with 2.67 GHz processor, and has a better identification accuracy than the compared algorithms MEME, AlignACE and VINE. Also, the validity of the proposed algorithm is tested on multiple real data sets.</div>
</front>
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