MotifClick: prediction of cis-regulatory binding sites via merging cliques
Identifieur interne : 000A90 ( Pmc/Curation ); précédent : 000A89; suivant : 000A91MotifClick: prediction of cis-regulatory binding sites via merging cliques
Auteurs : Shaoqiang Zhang [République populaire de Chine] ; Shan Li [États-Unis] ; Meng Niu [États-Unis] ; Phuc T. Pham [États-Unis] ; Zhengchang Su [États-Unis]Source :
- BMC Bioinformatics [ 1471-2105 ] ; 2011.
Abstract
Although dozens of algorithms and tools have been developed to find a set of
Here, we present a graph-based polynomial-time algorithm, MotifClick, for the prediction of
When evaluated on both synthetic and real datasets of prokaryotes and eukaryotes, MotifClick outperforms existing leading motif-finding tools for prediction accuracy and balancing the prediction sensitivity and specificity in general. In particular, when the distribution of nucleotides of binding sites is similar to that of their background sequences, MotifClick is more likely to identify the binding sites than the other tools.
Url:
DOI: 10.1186/1471-2105-12-238
PubMed: 21679436
PubMed Central: 3225181
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">MotifClick: prediction of <italic>cis</italic>-regulatory binding sites via merging cliques</title><author><name sortKey="Zhang, Shaoqiang" sort="Zhang, Shaoqiang" uniqKey="Zhang S" first="Shaoqiang" last="Zhang">Shaoqiang Zhang</name><affiliation wicri:level="1"><nlm:aff id="I2">College of Computer and Information Engineering, Tianjin Normal University, 393 Bin Shui Xi Road, Tianjin, 300387, China</nlm:aff><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>College of Computer and Information Engineering, Tianjin Normal University, 393 Bin Shui Xi Road, Tianjin, 300387</wicri:regionArea></affiliation></author><author><name sortKey="Li, Shan" sort="Li, Shan" uniqKey="Li S" first="Shan" last="Li">Shan Li</name><affiliation wicri:level="1"><nlm:aff id="I1">Department of Bioinformatics and Genomics, Center for Bioinformatics Research, the University of North Carolina at Charlotte, 351 Bioinformatics Building, 9201 University City Blvd., Charlotte, NC 28223, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Bioinformatics and Genomics, Center for Bioinformatics Research, the University of North Carolina at Charlotte, 351 Bioinformatics Building, 9201 University City Blvd., Charlotte, NC 28223</wicri:regionArea></affiliation></author><author><name sortKey="Niu, Meng" sort="Niu, Meng" uniqKey="Niu M" first="Meng" last="Niu">Meng Niu</name><affiliation wicri:level="1"><nlm:aff id="I1">Department of Bioinformatics and Genomics, Center for Bioinformatics Research, the University of North Carolina at Charlotte, 351 Bioinformatics Building, 9201 University City Blvd., Charlotte, NC 28223, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Bioinformatics and Genomics, Center for Bioinformatics Research, the University of North Carolina at Charlotte, 351 Bioinformatics Building, 9201 University City Blvd., Charlotte, NC 28223</wicri:regionArea></affiliation></author><author><name sortKey="Pham, Phuc T" sort="Pham, Phuc T" uniqKey="Pham P" first="Phuc T" last="Pham">Phuc T. Pham</name><affiliation wicri:level="1"><nlm:aff id="I1">Department of Bioinformatics and Genomics, Center for Bioinformatics Research, the University of North Carolina at Charlotte, 351 Bioinformatics Building, 9201 University City Blvd., Charlotte, NC 28223, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Bioinformatics and Genomics, Center for Bioinformatics Research, the University of North Carolina at Charlotte, 351 Bioinformatics Building, 9201 University City Blvd., Charlotte, NC 28223</wicri:regionArea></affiliation></author><author><name sortKey="Su, Zhengchang" sort="Su, Zhengchang" uniqKey="Su Z" first="Zhengchang" last="Su">Zhengchang Su</name><affiliation wicri:level="1"><nlm:aff id="I1">Department of Bioinformatics and Genomics, Center for Bioinformatics Research, the University of North Carolina at Charlotte, 351 Bioinformatics Building, 9201 University City Blvd., Charlotte, NC 28223, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Bioinformatics and Genomics, Center for Bioinformatics Research, the University of North Carolina at Charlotte, 351 Bioinformatics Building, 9201 University City Blvd., Charlotte, NC 28223</wicri:regionArea></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">21679436</idno><idno type="pmc">3225181</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3225181</idno><idno type="RBID">PMC:3225181</idno><idno type="doi">10.1186/1471-2105-12-238</idno><date when="2011">2011</date><idno type="wicri:Area/Pmc/Corpus">000A90</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000A90</idno><idno type="wicri:Area/Pmc/Curation">000A90</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Curation">000A90</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">MotifClick: prediction of <italic>cis</italic>-regulatory binding sites via merging cliques</title><author><name sortKey="Zhang, Shaoqiang" sort="Zhang, Shaoqiang" uniqKey="Zhang S" first="Shaoqiang" last="Zhang">Shaoqiang Zhang</name><affiliation wicri:level="1"><nlm:aff id="I2">College of Computer and Information Engineering, Tianjin Normal University, 393 Bin Shui Xi Road, Tianjin, 300387, China</nlm:aff><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>College of Computer and Information Engineering, Tianjin Normal University, 393 Bin Shui Xi Road, Tianjin, 300387</wicri:regionArea></affiliation></author><author><name sortKey="Li, Shan" sort="Li, Shan" uniqKey="Li S" first="Shan" last="Li">Shan Li</name><affiliation wicri:level="1"><nlm:aff id="I1">Department of Bioinformatics and Genomics, Center for Bioinformatics Research, the University of North Carolina at Charlotte, 351 Bioinformatics Building, 9201 University City Blvd., Charlotte, NC 28223, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Bioinformatics and Genomics, Center for Bioinformatics Research, the University of North Carolina at Charlotte, 351 Bioinformatics Building, 9201 University City Blvd., Charlotte, NC 28223</wicri:regionArea></affiliation></author><author><name sortKey="Niu, Meng" sort="Niu, Meng" uniqKey="Niu M" first="Meng" last="Niu">Meng Niu</name><affiliation wicri:level="1"><nlm:aff id="I1">Department of Bioinformatics and Genomics, Center for Bioinformatics Research, the University of North Carolina at Charlotte, 351 Bioinformatics Building, 9201 University City Blvd., Charlotte, NC 28223, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Bioinformatics and Genomics, Center for Bioinformatics Research, the University of North Carolina at Charlotte, 351 Bioinformatics Building, 9201 University City Blvd., Charlotte, NC 28223</wicri:regionArea></affiliation></author><author><name sortKey="Pham, Phuc T" sort="Pham, Phuc T" uniqKey="Pham P" first="Phuc T" last="Pham">Phuc T. Pham</name><affiliation wicri:level="1"><nlm:aff id="I1">Department of Bioinformatics and Genomics, Center for Bioinformatics Research, the University of North Carolina at Charlotte, 351 Bioinformatics Building, 9201 University City Blvd., Charlotte, NC 28223, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Bioinformatics and Genomics, Center for Bioinformatics Research, the University of North Carolina at Charlotte, 351 Bioinformatics Building, 9201 University City Blvd., Charlotte, NC 28223</wicri:regionArea></affiliation></author><author><name sortKey="Su, Zhengchang" sort="Su, Zhengchang" uniqKey="Su Z" first="Zhengchang" last="Su">Zhengchang Su</name><affiliation wicri:level="1"><nlm:aff id="I1">Department of Bioinformatics and Genomics, Center for Bioinformatics Research, the University of North Carolina at Charlotte, 351 Bioinformatics Building, 9201 University City Blvd., Charlotte, NC 28223, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Bioinformatics and Genomics, Center for Bioinformatics Research, the University of North Carolina at Charlotte, 351 Bioinformatics Building, 9201 University City Blvd., Charlotte, NC 28223</wicri:regionArea></affiliation></author></analytic><series><title level="j">BMC Bioinformatics</title><idno type="eISSN">1471-2105</idno><imprint><date when="2011">2011</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>Background</title><p>Although dozens of algorithms and tools have been developed to find a set of <italic>cis</italic>-regulatory binding sites called a motif in a set of intergenic sequences using various approaches, most of these tools focus on identifying binding sites that are significantly different from their background sequences. However, some motifs may have a similar nucleotide distribution to that of their background sequences. Therefore, such binding sites can be missed by these tools.</p></sec><sec><title>Results</title><p>Here, we present a graph-based polynomial-time algorithm, MotifClick, for the prediction of <italic>cis</italic>-regulatory binding sites, in particular, those that have a similar nucleotide distribution to that of their background sequences. To find binding sites with length <italic>k</italic>, we construct a graph using some 2(<italic>k</italic>-1)-mers in the input sequences as the vertices, and connect two vertices by an edge if the maximum number of matches of the local gapless alignments between the two 2(<italic>k</italic>-1)-mers is greater than a cutoff value. We identify a motif as a set of similar <italic>k</italic>-mers from a merged group of maximum cliques associated with some vertices.</p></sec><sec><title>Conclusions</title><p>When evaluated on both synthetic and real datasets of prokaryotes and eukaryotes, MotifClick outperforms existing leading motif-finding tools for prediction accuracy and balancing the prediction sensitivity and specificity in general. In particular, when the distribution of nucleotides of binding sites is similar to that of their background sequences, MotifClick is more likely to identify the binding sites than the other tools.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Kim, Hd" uniqKey="Kim H">HD Kim</name></author><author><name sortKey="Shay, T" uniqKey="Shay T">T Shay</name></author><author><name sortKey="O Shea, Ek" uniqKey="O Shea E">EK O'Shea</name></author><author><name sortKey="Regev, A" uniqKey="Regev A">A Regev</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Reed, Jl" uniqKey="Reed J">JL Reed</name></author><author><name sortKey="Famili, I" uniqKey="Famili I">I Famili</name></author><author><name sortKey="Thiele, I" uniqKey="Thiele I">I Thiele</name></author><author><name sortKey="Palsson, Bo" uniqKey="Palsson B">BO Palsson</name></author></analytic></biblStruct><biblStruct><analytic><author><name 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<front><journal-meta><journal-id journal-id-type="nlm-ta">BMC Bioinformatics</journal-id><journal-title-group><journal-title>BMC Bioinformatics</journal-title></journal-title-group><issn pub-type="epub">1471-2105</issn><publisher><publisher-name>BioMed Central</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">21679436</article-id><article-id pub-id-type="pmc">3225181</article-id><article-id pub-id-type="publisher-id">1471-2105-12-238</article-id><article-id pub-id-type="doi">10.1186/1471-2105-12-238</article-id><article-categories><subj-group subj-group-type="heading"><subject>Methodology Article</subject></subj-group></article-categories><title-group><article-title>MotifClick: prediction of <italic>cis</italic>-regulatory binding sites via merging cliques</article-title></title-group><contrib-group><contrib contrib-type="author" id="A1"><name><surname>Zhang</surname><given-names>Shaoqiang</given-names></name><xref ref-type="aff" rid="I2">2</xref><email>sqzhang@163.com</email></contrib><contrib contrib-type="author" id="A2"><name><surname>Li</surname><given-names>Shan</given-names></name><xref ref-type="aff" rid="I1">1</xref><email>sli13@uncc.edu</email></contrib><contrib contrib-type="author" id="A3"><name><surname>Niu</surname><given-names>Meng</given-names></name><xref ref-type="aff" rid="I1">1</xref><email>mniu2@uncc.edu</email></contrib><contrib contrib-type="author" id="A4"><name><surname>Pham</surname><given-names>Phuc T</given-names></name><xref ref-type="aff" rid="I1">1</xref><email>ptpham@uncc.edu</email></contrib><contrib contrib-type="author" corresp="yes" id="A5"><name><surname>Su</surname><given-names>Zhengchang</given-names></name><xref ref-type="aff" rid="I1">1</xref><email>zcsu@uncc.edu</email></contrib></contrib-group><aff id="I1"><label>1</label>Department of Bioinformatics and Genomics, Center for Bioinformatics Research, the University of North Carolina at Charlotte, 351 Bioinformatics Building, 9201 University City Blvd., Charlotte, NC 28223, USA</aff><aff id="I2"><label>2</label>College of Computer and Information Engineering, Tianjin Normal University, 393 Bin Shui Xi Road, Tianjin, 300387, China</aff><pub-date pub-type="collection"><year>2011</year></pub-date><pub-date pub-type="epub"><day>16</day><month>6</month><year>2011</year></pub-date><volume>12</volume><fpage>238</fpage><lpage>238</lpage><history><date date-type="received"><day>23</day><month>12</month><year>2010</year></date><date date-type="accepted"><day>16</day><month>6</month><year>2011</year></date></history><permissions><copyright-statement>Copyright ©2011 Zhang et al; licensee BioMed Central Ltd.</copyright-statement><copyright-year>2011</copyright-year><copyright-holder>Zhang et al; licensee BioMed Central Ltd.</copyright-holder><license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/2.0"><license-p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/2.0">http://creativecommons.org/licenses/by/2.0</ext-link>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p></license></permissions><self-uri xlink:href="http://www.biomedcentral.com/1471-2105/12/238"></self-uri><abstract><sec><title>Background</title><p>Although dozens of algorithms and tools have been developed to find a set of <italic>cis</italic>-regulatory binding sites called a motif in a set of intergenic sequences using various approaches, most of these tools focus on identifying binding sites that are significantly different from their background sequences. However, some motifs may have a similar nucleotide distribution to that of their background sequences. Therefore, such binding sites can be missed by these tools.</p></sec><sec><title>Results</title><p>Here, we present a graph-based polynomial-time algorithm, MotifClick, for the prediction of <italic>cis</italic>-regulatory binding sites, in particular, those that have a similar nucleotide distribution to that of their background sequences. To find binding sites with length <italic>k</italic>, we construct a graph using some 2(<italic>k</italic>-1)-mers in the input sequences as the vertices, and connect two vertices by an edge if the maximum number of matches of the local gapless alignments between the two 2(<italic>k</italic>-1)-mers is greater than a cutoff value. We identify a motif as a set of similar <italic>k</italic>-mers from a merged group of maximum cliques associated with some vertices.</p></sec><sec><title>Conclusions</title><p>When evaluated on both synthetic and real datasets of prokaryotes and eukaryotes, MotifClick outperforms existing leading motif-finding tools for prediction accuracy and balancing the prediction sensitivity and specificity in general. In particular, when the distribution of nucleotides of binding sites is similar to that of their background sequences, MotifClick is more likely to identify the binding sites than the other tools.</p></sec></abstract></article-meta></front></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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