A fast and robust iterative algorithm for prediction of RNA pseudoknotted secondary structures
Identifieur interne : 000392 ( Pmc/Curation ); précédent : 000391; suivant : 000393A fast and robust iterative algorithm for prediction of RNA pseudoknotted secondary structures
Auteurs : Hosna Jabbari [Canada] ; Anne Condon [Canada]Source :
- BMC Bioinformatics [ 1471-2105 ] ; 2014.
Abstract
Improving accuracy and efficiency of computational methods that predict pseudoknotted RNA secondary structures is an ongoing challenge. Existing methods based on free energy minimization tend to be very slow and are limited in the types of pseudoknots that they can predict. Incorporating known structural information can improve prediction accuracy; however, there are not many methods for prediction of pseudoknotted structures that can incorporate structural information as input. There is even less understanding of the relative robustness of these methods with respect to partial information.
We present a new method, Iterative HFold, for pseudoknotted RNA secondary structure prediction. Iterative HFold takes as input a pseudoknot-free structure, and produces a possibly pseudoknotted structure whose energy is at least as low as that of any (density-2) pseudoknotted structure containing the input structure. Iterative HFold leverages strengths of earlier methods, namely the fast running time of HFold, a method that is based on the hierarchical folding hypothesis, and the energy parameters of HotKnots V2.0.
Our experimental evaluation on a large data set shows that Iterative HFold is robust with respect to partial information, with average accuracy on pseudoknotted structures steadily increasing from roughly 54% to 79% as the user provides up to 40% of the input structure.
Iterative HFold is much faster than HotKnots V2.0, while having comparable accuracy. Iterative HFold also has significantly better accuracy than IPknot on our HK-PK and IP-pk168 data sets.
Iterative HFold is a robust method for prediction of pseudoknotted RNA secondary structures, whose accuracy with more than 5% information about true pseudoknot-free structures is better than that of IPknot, and with about 35% information about true pseudoknot-free structures compares well with that of HotKnots V2.0 while being significantly faster. Iterative HFold and all data used in this work are freely available at
Url:
DOI: 10.1186/1471-2105-15-147
PubMed: 24884954
PubMed Central: 4064103
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">A fast and robust iterative algorithm for prediction of RNA pseudoknotted secondary structures</title><author><name sortKey="Jabbari, Hosna" sort="Jabbari, Hosna" uniqKey="Jabbari H" first="Hosna" last="Jabbari">Hosna Jabbari</name><affiliation wicri:level="1"><nlm:aff id="I1">Department of Computer Science, University of British Columbia, 2366 Main Mall, Vancouver, Canada</nlm:aff><country xml:lang="fr">Canada</country><wicri:regionArea>Department of Computer Science, University of British Columbia, 2366 Main Mall, Vancouver</wicri:regionArea></affiliation></author><author><name sortKey="Condon, Anne" sort="Condon, Anne" uniqKey="Condon A" first="Anne" last="Condon">Anne Condon</name><affiliation wicri:level="1"><nlm:aff id="I1">Department of Computer Science, University of British Columbia, 2366 Main Mall, Vancouver, Canada</nlm:aff><country xml:lang="fr">Canada</country><wicri:regionArea>Department of Computer Science, University of British Columbia, 2366 Main Mall, Vancouver</wicri:regionArea></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">24884954</idno><idno type="pmc">4064103</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4064103</idno><idno type="RBID">PMC:4064103</idno><idno type="doi">10.1186/1471-2105-15-147</idno><date when="2014">2014</date><idno type="wicri:Area/Pmc/Corpus">000392</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000392</idno><idno type="wicri:Area/Pmc/Curation">000392</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Curation">000392</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">A fast and robust iterative algorithm for prediction of RNA pseudoknotted secondary structures</title><author><name sortKey="Jabbari, Hosna" sort="Jabbari, Hosna" uniqKey="Jabbari H" first="Hosna" last="Jabbari">Hosna Jabbari</name><affiliation wicri:level="1"><nlm:aff id="I1">Department of Computer Science, University of British Columbia, 2366 Main Mall, Vancouver, Canada</nlm:aff><country xml:lang="fr">Canada</country><wicri:regionArea>Department of Computer Science, University of British Columbia, 2366 Main Mall, Vancouver</wicri:regionArea></affiliation></author><author><name sortKey="Condon, Anne" sort="Condon, Anne" uniqKey="Condon A" first="Anne" last="Condon">Anne Condon</name><affiliation wicri:level="1"><nlm:aff id="I1">Department of Computer Science, University of British Columbia, 2366 Main Mall, Vancouver, Canada</nlm:aff><country xml:lang="fr">Canada</country><wicri:regionArea>Department of Computer Science, University of British Columbia, 2366 Main Mall, Vancouver</wicri:regionArea></affiliation></author></analytic><series><title level="j">BMC Bioinformatics</title><idno type="eISSN">1471-2105</idno><imprint><date when="2014">2014</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>Background</title><p>Improving accuracy and efficiency of computational methods that predict pseudoknotted RNA secondary structures is an ongoing challenge. Existing methods based on free energy minimization tend to be very slow and are limited in the types of pseudoknots that they can predict. Incorporating known structural information can improve prediction accuracy; however, there are not many methods for prediction of pseudoknotted structures that can incorporate structural information as input. There is even less understanding of the relative robustness of these methods with respect to partial information.</p></sec><sec><title>Results</title><p>We present a new method, Iterative HFold, for pseudoknotted RNA secondary structure prediction. Iterative HFold takes as input a pseudoknot-free structure, and produces a possibly pseudoknotted structure whose energy is at least as low as that of any (density-2) pseudoknotted structure containing the input structure. Iterative HFold leverages strengths of earlier methods, namely the fast running time of HFold, a method that is based on the hierarchical folding hypothesis, and the energy parameters of HotKnots V2.0.</p><p>Our experimental evaluation on a large data set shows that Iterative HFold is robust with respect to partial information, with average accuracy on pseudoknotted structures steadily increasing from roughly 54% to 79% as the user provides up to 40% of the input structure.</p><p>Iterative HFold is much faster than HotKnots V2.0, while having comparable accuracy. Iterative HFold also has significantly better accuracy than IPknot on our HK-PK and IP-pk168 data sets.</p></sec><sec><title>Conclusions</title><p>Iterative HFold is a robust method for prediction of pseudoknotted RNA secondary structures, whose accuracy with more than 5% information about true pseudoknot-free structures is better than that of IPknot, and with about 35% information about true pseudoknot-free structures compares well with that of HotKnots V2.0 while being significantly faster. Iterative HFold and all data used in this work are freely available at <ext-link ext-link-type="uri" xlink:href="http://www.cs.ubc.ca/~hjabbari/software.php">http://www.cs.ubc.ca/~hjabbari/software.php</ext-link>.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Hale, Bj" uniqKey="Hale B">BJ Hale</name></author><author><name sortKey="Yang, C X" uniqKey="Yang C">C-X Yang</name></author><author><name sortKey="Ross, Jw" uniqKey="Ross J">JW Ross</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Deryusheva, S" uniqKey="Deryusheva S">S Deryusheva</name></author><author><name sortKey="Gall, Jg" uniqKey="Gall J">JG Gall</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Holt, Ce" uniqKey="Holt C">CE Holt</name></author><author><name sortKey="Schuman, Em" uniqKey="Schuman E">EM Schuman</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-id journal-id-type="iso-abbrev">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">24884954</article-id><article-id pub-id-type="pmc">4064103</article-id><article-id pub-id-type="publisher-id">1471-2105-15-147</article-id><article-id pub-id-type="doi">10.1186/1471-2105-15-147</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group></article-categories><title-group><article-title>A fast and robust iterative algorithm for prediction of RNA pseudoknotted secondary structures</article-title></title-group><contrib-group><contrib contrib-type="author" corresp="yes" id="A1"><name><surname>Jabbari</surname><given-names>Hosna</given-names></name><xref ref-type="aff" rid="I1">1</xref><email>hjabbari@cs.ubc.ca</email></contrib><contrib contrib-type="author" id="A2"><name><surname>Condon</surname><given-names>Anne</given-names></name><xref ref-type="aff" rid="I1">1</xref><email>condon@cs.ubc.ca</email></contrib></contrib-group><aff id="I1"><label>1</label>Department of Computer Science, University of British Columbia, 2366 Main Mall, Vancouver, Canada</aff><pub-date pub-type="collection"><year>2014</year></pub-date><pub-date pub-type="epub"><day>18</day><month>5</month><year>2014</year></pub-date><volume>15</volume><fpage>147</fpage><lpage>147</lpage><history><date date-type="received"><day>7</day><month>1</month><year>2014</year></date><date date-type="accepted"><day>8</day><month>5</month><year>2014</year></date></history><permissions><copyright-statement>Copyright © 2014 Jabbari and Condon; licensee BioMed Central Ltd.</copyright-statement><copyright-year>2014</copyright-year><copyright-holder>Jabbari and Condon; 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 credited. The Creative Commons Public Domain Dedication waiver (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/publicdomain/zero/1.0/">http://creativecommons.org/publicdomain/zero/1.0/</ext-link>) applies to the data made available in this article, unless otherwise stated.</license-p></license></permissions><self-uri xlink:href="http://www.biomedcentral.com/1471-2105/15/147"></self-uri><abstract><sec><title>Background</title><p>Improving accuracy and efficiency of computational methods that predict pseudoknotted RNA secondary structures is an ongoing challenge. Existing methods based on free energy minimization tend to be very slow and are limited in the types of pseudoknots that they can predict. Incorporating known structural information can improve prediction accuracy; however, there are not many methods for prediction of pseudoknotted structures that can incorporate structural information as input. There is even less understanding of the relative robustness of these methods with respect to partial information.</p></sec><sec><title>Results</title><p>We present a new method, Iterative HFold, for pseudoknotted RNA secondary structure prediction. Iterative HFold takes as input a pseudoknot-free structure, and produces a possibly pseudoknotted structure whose energy is at least as low as that of any (density-2) pseudoknotted structure containing the input structure. Iterative HFold leverages strengths of earlier methods, namely the fast running time of HFold, a method that is based on the hierarchical folding hypothesis, and the energy parameters of HotKnots V2.0.</p><p>Our experimental evaluation on a large data set shows that Iterative HFold is robust with respect to partial information, with average accuracy on pseudoknotted structures steadily increasing from roughly 54% to 79% as the user provides up to 40% of the input structure.</p><p>Iterative HFold is much faster than HotKnots V2.0, while having comparable accuracy. Iterative HFold also has significantly better accuracy than IPknot on our HK-PK and IP-pk168 data sets.</p></sec><sec><title>Conclusions</title><p>Iterative HFold is a robust method for prediction of pseudoknotted RNA secondary structures, whose accuracy with more than 5% information about true pseudoknot-free structures is better than that of IPknot, and with about 35% information about true pseudoknot-free structures compares well with that of HotKnots V2.0 while being significantly faster. Iterative HFold and all data used in this work are freely available at <ext-link ext-link-type="uri" xlink:href="http://www.cs.ubc.ca/~hjabbari/software.php">http://www.cs.ubc.ca/~hjabbari/software.php</ext-link>.</p></sec></abstract><kwd-group><kwd>RNA</kwd><kwd>Secondary structure prediction</kwd><kwd>Pseudoknot</kwd><kwd>Hierarchical folding</kwd><kwd>Minimum free energy</kwd></kwd-group></article-meta></front></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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