IntelliGO: a new vector-based semantic similarity measure including annotation origin
Identifieur interne : 000075 ( Pmc/Curation ); précédent : 000074; suivant : 000076IntelliGO: a new vector-based semantic similarity measure including annotation origin
Auteurs : Sidahmed Benabderrahmane [France] ; Malika Smail-Tabbone [France] ; Olivier Poch [France] ; Amedeo Napoli [France] ; Marie-Dominique Devignes [France]Source :
- BMC Bioinformatics [ 1471-2105 ] ; 2010.
Abstract
The Gene Ontology (GO) is a well known controlled vocabulary describing the
We present here a new semantic similarity measure called
The
An on-line version of the
Url:
DOI: 10.1186/1471-2105-11-588
PubMed: 21122125
PubMed Central: 3098105
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Équipe Orpailleur, Bâtiment B, Campus scientifique, 54506 Vandoeuvre-lès-Nancy Cedex, France</nlm:aff><country xml:lang="fr">France</country><wicri:regionArea>LORIA (CNRS, INRIA, Nancy-Université), Équipe Orpailleur, Bâtiment B, Campus scientifique, 54506 Vandoeuvre-lès-Nancy Cedex</wicri:regionArea></affiliation></author><author><name sortKey="Poch, Olivier" sort="Poch, Olivier" uniqKey="Poch O" first="Olivier" last="Poch">Olivier Poch</name><affiliation wicri:level="1"><nlm:aff id="I2">L.B.G.I., CNRS UMR7104, IGBMC, 1 rue Laurent Fries, 67404 Illkirch Strasbourg, France</nlm:aff><country xml:lang="fr">France</country><wicri:regionArea>L.B.G.I., CNRS UMR7104, IGBMC, 1 rue Laurent Fries, 67404 Illkirch Strasbourg</wicri:regionArea></affiliation></author><author><name sortKey="Napoli, Amedeo" sort="Napoli, Amedeo" uniqKey="Napoli A" first="Amedeo" last="Napoli">Amedeo Napoli</name><affiliation wicri:level="1"><nlm:aff id="I1">LORIA (CNRS, INRIA, Nancy-Université), Équipe Orpailleur, Bâtiment B, Campus scientifique, 54506 Vandoeuvre-lès-Nancy Cedex, France</nlm:aff><country xml:lang="fr">France</country><wicri:regionArea>LORIA (CNRS, INRIA, Nancy-Université), Équipe Orpailleur, Bâtiment B, Campus scientifique, 54506 Vandoeuvre-lès-Nancy Cedex</wicri:regionArea></affiliation></author><author><name sortKey="Devignes, Marie Dominique" sort="Devignes, Marie Dominique" uniqKey="Devignes M" first="Marie-Dominique" last="Devignes">Marie-Dominique Devignes</name><affiliation wicri:level="1"><nlm:aff id="I1">LORIA (CNRS, INRIA, Nancy-Université), Équipe Orpailleur, Bâtiment B, Campus scientifique, 54506 Vandoeuvre-lès-Nancy Cedex, France</nlm:aff><country xml:lang="fr">France</country><wicri:regionArea>LORIA (CNRS, INRIA, Nancy-Université), Équipe Orpailleur, Bâtiment B, Campus scientifique, 54506 Vandoeuvre-lès-Nancy Cedex</wicri:regionArea></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">21122125</idno><idno type="pmc">3098105</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3098105</idno><idno type="RBID">PMC:3098105</idno><idno type="doi">10.1186/1471-2105-11-588</idno><date when="2010">2010</date><idno type="wicri:Area/Pmc/Corpus">000075</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000075</idno><idno type="wicri:Area/Pmc/Curation">000075</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Curation">000075</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">IntelliGO: a new vector-based semantic similarity measure including annotation origin</title><author><name sortKey="Benabderrahmane, Sidahmed" sort="Benabderrahmane, Sidahmed" uniqKey="Benabderrahmane S" first="Sidahmed" last="Benabderrahmane">Sidahmed Benabderrahmane</name><affiliation wicri:level="1"><nlm:aff id="I1">LORIA (CNRS, INRIA, Nancy-Université), Équipe Orpailleur, Bâtiment B, Campus scientifique, 54506 Vandoeuvre-lès-Nancy Cedex, France</nlm:aff><country xml:lang="fr">France</country><wicri:regionArea>LORIA (CNRS, INRIA, Nancy-Université), Équipe Orpailleur, Bâtiment B, Campus scientifique, 54506 Vandoeuvre-lès-Nancy Cedex</wicri:regionArea></affiliation></author><author><name sortKey="Smail Tabbone, Malika" sort="Smail Tabbone, Malika" uniqKey="Smail Tabbone M" first="Malika" last="Smail-Tabbone">Malika Smail-Tabbone</name><affiliation wicri:level="1"><nlm:aff id="I1">LORIA (CNRS, INRIA, Nancy-Université), Équipe Orpailleur, Bâtiment B, Campus scientifique, 54506 Vandoeuvre-lès-Nancy Cedex, France</nlm:aff><country xml:lang="fr">France</country><wicri:regionArea>LORIA (CNRS, INRIA, Nancy-Université), Équipe Orpailleur, Bâtiment B, Campus scientifique, 54506 Vandoeuvre-lès-Nancy Cedex</wicri:regionArea></affiliation></author><author><name sortKey="Poch, Olivier" sort="Poch, Olivier" uniqKey="Poch O" first="Olivier" last="Poch">Olivier Poch</name><affiliation wicri:level="1"><nlm:aff id="I2">L.B.G.I., CNRS UMR7104, IGBMC, 1 rue Laurent Fries, 67404 Illkirch Strasbourg, France</nlm:aff><country xml:lang="fr">France</country><wicri:regionArea>L.B.G.I., CNRS UMR7104, IGBMC, 1 rue Laurent Fries, 67404 Illkirch Strasbourg</wicri:regionArea></affiliation></author><author><name sortKey="Napoli, Amedeo" sort="Napoli, Amedeo" uniqKey="Napoli A" first="Amedeo" last="Napoli">Amedeo Napoli</name><affiliation wicri:level="1"><nlm:aff id="I1">LORIA (CNRS, INRIA, Nancy-Université), Équipe Orpailleur, Bâtiment B, Campus scientifique, 54506 Vandoeuvre-lès-Nancy Cedex, France</nlm:aff><country xml:lang="fr">France</country><wicri:regionArea>LORIA (CNRS, INRIA, Nancy-Université), Équipe Orpailleur, Bâtiment B, Campus scientifique, 54506 Vandoeuvre-lès-Nancy Cedex</wicri:regionArea></affiliation></author><author><name sortKey="Devignes, Marie Dominique" sort="Devignes, Marie Dominique" uniqKey="Devignes M" first="Marie-Dominique" last="Devignes">Marie-Dominique Devignes</name><affiliation wicri:level="1"><nlm:aff id="I1">LORIA (CNRS, INRIA, Nancy-Université), Équipe Orpailleur, Bâtiment B, Campus scientifique, 54506 Vandoeuvre-lès-Nancy Cedex, France</nlm:aff><country xml:lang="fr">France</country><wicri:regionArea>LORIA (CNRS, INRIA, Nancy-Université), Équipe Orpailleur, Bâtiment B, Campus scientifique, 54506 Vandoeuvre-lès-Nancy Cedex</wicri:regionArea></affiliation></author></analytic><series><title level="j">BMC Bioinformatics</title><idno type="eISSN">1471-2105</idno><imprint><date when="2010">2010</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>Background</title><p>The Gene Ontology (GO) is a well known controlled vocabulary describing the <italic>biological process</italic>, <italic>molecular function </italic>and <italic>cellular component </italic>aspects of gene annotation. It has become a widely used knowledge source in bioinformatics for annotating genes and measuring their semantic similarity. These measures generally involve the GO graph structure, the information content of GO aspects, or a combination of both. However, only a few of the semantic similarity measures described so far can handle GO annotations differently according to their origin (<italic>i.e</italic>. their evidence codes).</p></sec><sec><title>Results</title><p>We present here a new semantic similarity measure called <italic>IntelliGO </italic>which integrates several complementary properties in a novel vector space model. The coefficients associated with each GO term that annotates a given gene or protein include its information content as well as a customized value for each type of GO evidence code. The generalized cosine similarity measure, used for calculating the dot product between two vectors, has been rigorously adapted to the context of the GO graph. The <italic>IntelliGO </italic>similarity measure is tested on two benchmark datasets consisting of KEGG pathways and Pfam domains grouped as clans, considering the GO <italic>biological process </italic>and <italic>molecular function </italic>terms, respectively, for a total of 683 yeast and human genes and involving more than 67,900 pair-wise comparisons. The ability of the <italic>IntelliGO </italic>similarity measure to express the biological cohesion of sets of genes compares favourably to four existing similarity measures. For inter-set comparison, it consistently discriminates between distinct sets of genes. Furthermore, the <italic>IntelliGO </italic>similarity measure allows the influence of weights assigned to evidence codes to be checked. Finally, the results obtained with a complementary reference technique give intermediate but correct correlation values with the sequence similarity, Pfam, and Enzyme classifications when compared to previously published measures.</p></sec><sec><title>Conclusions</title><p>The <italic>IntelliGO </italic>similarity measure provides a customizable and comprehensive method for quantifying gene similarity based on GO annotations. It also displays a robust set-discriminating power which suggests it will be useful for functional clustering.</p></sec><sec><title>Availability</title><p>An on-line version of the <italic>IntelliGO </italic>similarity measure is available at: <ext-link ext-link-type="uri" xlink:href="http://bioinfo.loria.fr/Members/benabdsi/intelligo_project/">http://bioinfo.loria.fr/Members/benabdsi/intelligo_project/</ext-link></p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Ashburner, M" uniqKey="Ashburner M">M Ashburner</name></author><author><name sortKey="Ball, C" uniqKey="Ball C">C Ball</name></author><author><name sortKey="Blake, J" uniqKey="Blake J">J Blake</name></author><author><name sortKey="Botstein, D" uniqKey="Botstein D">D Botstein</name></author><author><name sortKey="Butler, H" uniqKey="Butler H">H Butler</name></author><author><name sortKey="Cherry, M" uniqKey="Cherry M">M Cherry</name></author><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">21122125</article-id><article-id pub-id-type="pmc">3098105</article-id><article-id pub-id-type="publisher-id">1471-2105-11-588</article-id><article-id pub-id-type="doi">10.1186/1471-2105-11-588</article-id><article-categories><subj-group subj-group-type="heading"><subject>Methodology Article</subject></subj-group></article-categories><title-group><article-title>IntelliGO: a new vector-based semantic similarity measure including annotation origin</article-title></title-group><contrib-group><contrib contrib-type="author" corresp="yes" id="A1"><name><surname>Benabderrahmane</surname><given-names>Sidahmed</given-names></name><xref ref-type="aff" rid="I1">1</xref><email>benabdsi@loria.fr</email></contrib><contrib contrib-type="author" id="A2"><name><surname>Smail-Tabbone</surname><given-names>Malika</given-names></name><xref ref-type="aff" rid="I1">1</xref><email>malika@loria.fr</email></contrib><contrib contrib-type="author" id="A3"><name><surname>Poch</surname><given-names>Olivier</given-names></name><xref ref-type="aff" rid="I2">2</xref><email>poch@titus.u-strasbg.fr</email></contrib><contrib contrib-type="author" id="A4"><name><surname>Napoli</surname><given-names>Amedeo</given-names></name><xref ref-type="aff" rid="I1">1</xref><email>napoli@loria.fr</email></contrib><contrib contrib-type="author" id="A5"><name><surname>Devignes</surname><given-names>Marie-Dominique</given-names></name><xref ref-type="aff" rid="I1">1</xref><email>devignes@loria.fr</email></contrib></contrib-group><aff id="I1"><label>1</label>LORIA (CNRS, INRIA, Nancy-Université), Équipe Orpailleur, Bâtiment B, Campus scientifique, 54506 Vandoeuvre-lès-Nancy Cedex, France</aff><aff id="I2"><label>2</label>L.B.G.I., CNRS UMR7104, IGBMC, 1 rue Laurent Fries, 67404 Illkirch Strasbourg, France</aff><pub-date pub-type="collection"><year>2010</year></pub-date><pub-date pub-type="epub"><day>1</day><month>12</month><year>2010</year></pub-date><volume>11</volume><fpage>588</fpage><lpage>588</lpage><history><date date-type="received"><day>19</day><month>5</month><year>2010</year></date><date date-type="accepted"><day>1</day><month>12</month><year>2010</year></date></history><permissions><copyright-statement>Copyright ©2010 Benabderrahmane et al; licensee BioMed Central Ltd.</copyright-statement><copyright-year>2010</copyright-year><copyright-holder>Benabderrahmane et al; licensee BioMed Central Ltd.</copyright-holder><license license-type="open-access"><license-p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0 ), 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/1471-2105/11/588"></self-uri><abstract><sec><title>Background</title><p>The Gene Ontology (GO) is a well known controlled vocabulary describing the <italic>biological process</italic>, <italic>molecular function </italic>and <italic>cellular component </italic>aspects of gene annotation. It has become a widely used knowledge source in bioinformatics for annotating genes and measuring their semantic similarity. These measures generally involve the GO graph structure, the information content of GO aspects, or a combination of both. However, only a few of the semantic similarity measures described so far can handle GO annotations differently according to their origin (<italic>i.e</italic>. their evidence codes).</p></sec><sec><title>Results</title><p>We present here a new semantic similarity measure called <italic>IntelliGO </italic>which integrates several complementary properties in a novel vector space model. The coefficients associated with each GO term that annotates a given gene or protein include its information content as well as a customized value for each type of GO evidence code. The generalized cosine similarity measure, used for calculating the dot product between two vectors, has been rigorously adapted to the context of the GO graph. The <italic>IntelliGO </italic>similarity measure is tested on two benchmark datasets consisting of KEGG pathways and Pfam domains grouped as clans, considering the GO <italic>biological process </italic>and <italic>molecular function </italic>terms, respectively, for a total of 683 yeast and human genes and involving more than 67,900 pair-wise comparisons. The ability of the <italic>IntelliGO </italic>similarity measure to express the biological cohesion of sets of genes compares favourably to four existing similarity measures. For inter-set comparison, it consistently discriminates between distinct sets of genes. Furthermore, the <italic>IntelliGO </italic>similarity measure allows the influence of weights assigned to evidence codes to be checked. Finally, the results obtained with a complementary reference technique give intermediate but correct correlation values with the sequence similarity, Pfam, and Enzyme classifications when compared to previously published measures.</p></sec><sec><title>Conclusions</title><p>The <italic>IntelliGO </italic>similarity measure provides a customizable and comprehensive method for quantifying gene similarity based on GO annotations. It also displays a robust set-discriminating power which suggests it will be useful for functional clustering.</p></sec><sec><title>Availability</title><p>An on-line version of the <italic>IntelliGO </italic>similarity measure is available at: <ext-link ext-link-type="uri" xlink:href="http://bioinfo.loria.fr/Members/benabdsi/intelligo_project/">http://bioinfo.loria.fr/Members/benabdsi/intelligo_project/</ext-link></p></sec></abstract></article-meta></front></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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