Integration and publication of heterogeneous text-mined relationships on the Semantic Web
Identifieur interne : 000079 ( Pmc/Curation ); précédent : 000078; suivant : 000080Integration and publication of heterogeneous text-mined relationships on the Semantic Web
Auteurs : Adrien Coulet [France, États-Unis] ; Yael Garten [États-Unis] ; Michel Dumontier ; Russ B. Altman [États-Unis] ; Mark A. Musen [États-Unis] ; Nigam H. Shah [États-Unis]Source :
- Journal of Biomedical Semantics [ 2041-1480 ] ; 2011.
Abstract
Advances in Natural Language Processing (NLP) techniques enable the extraction of fine-grained relationships mentioned in biomedical text. The variability and the complexity of natural language in expressing similar relationships causes the extracted relationships to be highly heterogeneous, which makes the construction of knowledge bases difficult and poses a challenge in using these for data mining or question answering.
We report on the semi-automatic construction of the PHARE relationship ontology (the PHArmacogenomic RElationships Ontology) consisting of 200 curated relations from over 40,000 heterogeneous relationships extracted via text-mining. These heterogeneous relations are then mapped to the PHARE ontology using synonyms, entity descriptions and hierarchies of entities and roles. Once mapped, relationships can be normalized and compared using the structure of the ontology to identify relationships that have similar semantics but different syntax. We compare and contrast the manual procedure with a fully automated approach using WordNet to quantify the degree of integration enabled by iterative curation and refinement of the PHARE ontology. The result of such integration is a repository of normalized biomedical relationships, named PHARE-KB, which can be queried using Semantic Web technologies such as SPARQL and can be visualized in the form of a biological network.
The PHARE ontology serves as a common semantic framework to integrate more than 40,000 relationships pertinent to pharmacogenomics. The PHARE ontology forms the foundation of a knowledge base named PHARE-KB. Once populated with relationships, PHARE-KB (
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DOI: 10.1186/2041-1480-2-S2-S10
PubMed: 21624156
PubMed Central: 3102890
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Michel Dumontier<affiliation><nlm:aff id="I4">Department of Biology, Carleton University, 1125 Colonel By Drive, Ottawa, ON, Canada, K1S5B6</nlm:aff><wicri:noCountry code="subfield">K1S5B6</wicri:noCountry></affiliation>Le document en format XML
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Altman</name><affiliation wicri:level="1"><nlm:aff id="I2">Department of Medicine, 300 Pasteur Drive, Mail Code 5110, Stanford University, Stanford, CA, 94305, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Medicine, 300 Pasteur Drive, Mail Code 5110, Stanford University, Stanford, CA, 94305</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="I3">Department of Genetics, Mail Code 5120, Stanford University, Stanford, CA, 94305, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Genetics, Mail Code 5120, Stanford University, Stanford, CA, 94305</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="I5">Department of Bioengineering, 318 Campus Drive, Mail Code 5444, Stanford University, Stanford, CA, 94305, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Bioengineering, 318 Campus Drive, Mail Code 5444, Stanford University, Stanford, CA, 94305</wicri:regionArea></affiliation></author><author><name sortKey="Musen, Mark A" sort="Musen, Mark A" uniqKey="Musen M" first="Mark A" last="Musen">Mark A. Musen</name><affiliation wicri:level="1"><nlm:aff id="I2">Department of Medicine, 300 Pasteur Drive, Mail Code 5110, Stanford University, Stanford, CA, 94305, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Medicine, 300 Pasteur Drive, Mail Code 5110, Stanford University, Stanford, CA, 94305</wicri:regionArea></affiliation></author><author><name sortKey="Shah, Nigam H" sort="Shah, Nigam H" uniqKey="Shah N" first="Nigam H" last="Shah">Nigam H. Shah</name><affiliation wicri:level="1"><nlm:aff id="I2">Department of Medicine, 300 Pasteur Drive, Mail Code 5110, Stanford University, Stanford, CA, 94305, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Medicine, 300 Pasteur Drive, Mail Code 5110, Stanford University, Stanford, CA, 94305</wicri:regionArea></affiliation></author></analytic><series><title level="j">Journal of Biomedical Semantics</title><idno type="eISSN">2041-1480</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>Advances in Natural Language Processing (NLP) techniques enable the extraction of fine-grained relationships mentioned in biomedical text. The variability and the complexity of natural language in expressing similar relationships causes the extracted relationships to be highly heterogeneous, which makes the construction of knowledge bases difficult and poses a challenge in using these for data mining or question answering.</p></sec><sec><title>Results</title><p>We report on the semi-automatic construction of the PHARE relationship ontology (the PHArmacogenomic RElationships Ontology) consisting of 200 curated relations from over 40,000 heterogeneous relationships extracted via text-mining. These heterogeneous relations are then mapped to the PHARE ontology using synonyms, entity descriptions and hierarchies of entities and roles. Once mapped, relationships can be normalized and compared using the structure of the ontology to identify relationships that have similar semantics but different syntax. We compare and contrast the manual procedure with a fully automated approach using WordNet to quantify the degree of integration enabled by iterative curation and refinement of the PHARE ontology. The result of such integration is a repository of normalized biomedical relationships, named PHARE-KB, which can be queried using Semantic Web technologies such as SPARQL and can be visualized in the form of a biological network.</p></sec><sec><title>Conclusions</title><p>The PHARE ontology serves as a common semantic framework to integrate more than 40,000 relationships pertinent to pharmacogenomics. The PHARE ontology forms the foundation of a knowledge base named PHARE-KB. Once populated with relationships, PHARE-KB (<italic>i</italic>) can be visualized in the form of a biological network to guide human tasks such as database curation and (<italic>ii</italic>) can be queried programmatically to guide bioinformatics applications such as the prediction of molecular interactions. PHARE is available at <ext-link ext-link-type="uri" xlink:href="http://purl.bioontology.org/ontology/PHARE">http://purl.bioontology.org/ontology/PHARE</ext-link>.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Groth, P" uniqKey="Groth P">P Groth</name></author><author><name sortKey="Gibson, A" uniqKey="Gibson A">A Gibson</name></author><author><name sortKey="Velterop, J" uniqKey="Velterop J">J Velterop</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Klein, T" uniqKey="Klein T">T Klein</name></author><author><name sortKey="Chang, J" uniqKey="Chang J">J Chang</name></author><author><name sortKey="Cho, M" uniqKey="Cho M">M Cho</name></author><author><name sortKey="Easton, K" uniqKey="Easton K">K Easton</name></author><author><name sortKey="Fergerson, K" uniqKey="Fergerson K">K Fergerson</name></author><author><name sortKey="Hewett, M" uniqKey="Hewett M">M Hewett</name></author><author><name 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<front><journal-meta><journal-id journal-id-type="nlm-ta">J Biomed Semantics</journal-id><journal-title-group><journal-title>Journal of Biomedical Semantics</journal-title></journal-title-group><issn pub-type="epub">2041-1480</issn><publisher><publisher-name>BioMed Central</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">21624156</article-id><article-id pub-id-type="pmc">3102890</article-id><article-id pub-id-type="publisher-id">2041-1480-2-S2-S10</article-id><article-id pub-id-type="doi">10.1186/2041-1480-2-S2-S10</article-id><article-categories><subj-group subj-group-type="heading"><subject>Proceedings</subject></subj-group></article-categories><title-group><article-title>Integration and publication of heterogeneous text-mined relationships on the Semantic Web</article-title></title-group><contrib-group><contrib contrib-type="author" corresp="yes" id="A1"><name><surname>Coulet</surname><given-names>Adrien</given-names></name><xref ref-type="aff" rid="I1">1</xref><xref ref-type="aff" rid="I2">2</xref><xref ref-type="aff" rid="I3">3</xref><email>adrien.coulet@loria.fr</email></contrib><contrib contrib-type="author" id="A2"><name><surname>Garten</surname><given-names>Yael</given-names></name><xref ref-type="aff" rid="I2">2</xref><xref ref-type="aff" rid="I3">3</xref><email>ygarten@stanford.edu</email></contrib><contrib contrib-type="author" id="A3"><name><surname>Dumontier</surname><given-names>Michel</given-names></name><xref ref-type="aff" rid="I4">4</xref><email>michel_dumontier@carlton.ca</email></contrib><contrib contrib-type="author" id="A4"><name><surname>Altman</surname><given-names>Russ B</given-names></name><xref ref-type="aff" rid="I2">2</xref><xref ref-type="aff" rid="I3">3</xref><xref ref-type="aff" rid="I5">5</xref><email>russ.altman@stanford.edu</email></contrib><contrib contrib-type="author" id="A5"><name><surname>Musen</surname><given-names>Mark A</given-names></name><xref ref-type="aff" rid="I2">2</xref><email>musen@stanford.edu</email></contrib><contrib contrib-type="author" id="A6"><name><surname>Shah</surname><given-names>Nigam H</given-names></name><xref ref-type="aff" rid="I2">2</xref><email>nigam@stanford.edu</email></contrib></contrib-group><aff id="I1"><label>1</label>LORIA – INRIA Nancy – Grand-Est, Campus Scientifique - BP 239 - 54506 Vandoeuvre-lès-Nancy Cedex, France</aff><aff id="I2"><label>2</label>Department of Medicine, 300 Pasteur Drive, Mail Code 5110, Stanford University, Stanford, CA, 94305, USA</aff><aff id="I3"><label>3</label>Department of Genetics, Mail Code 5120, Stanford University, Stanford, CA, 94305, USA</aff><aff id="I4"><label>4</label>Department of Biology, Carleton University, 1125 Colonel By Drive, Ottawa, ON, Canada, K1S5B6</aff><aff id="I5"><label>5</label>Department of Bioengineering, 318 Campus Drive, Mail Code 5444, Stanford University, Stanford, CA, 94305, USA</aff><pub-date pub-type="collection"><year>2011</year></pub-date><pub-date pub-type="epub"><day>17</day><month>5</month><year>2011</year></pub-date><volume>2</volume><issue>Suppl 2</issue><supplement><named-content content-type="supplement-title">Proceedings of the Bio-Ontologies Special Interest Group Meeting 2010</named-content><named-content content-type="supplement-editor">Larisa Soldatova, Susanna-Assunta Sansone, Susie Stephens and Nigam H Shah</named-content></supplement><fpage>S10</fpage><lpage>S10</lpage><permissions><copyright-statement>Copyright ©2011 Coulet et al; licensee BioMed Central Ltd.</copyright-statement><copyright-year>2011</copyright-year><copyright-holder>Coulet 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.jbiomedsem.com/content/2/S2/S10"></self-uri><abstract><sec><title>Background</title><p>Advances in Natural Language Processing (NLP) techniques enable the extraction of fine-grained relationships mentioned in biomedical text. The variability and the complexity of natural language in expressing similar relationships causes the extracted relationships to be highly heterogeneous, which makes the construction of knowledge bases difficult and poses a challenge in using these for data mining or question answering.</p></sec><sec><title>Results</title><p>We report on the semi-automatic construction of the PHARE relationship ontology (the PHArmacogenomic RElationships Ontology) consisting of 200 curated relations from over 40,000 heterogeneous relationships extracted via text-mining. These heterogeneous relations are then mapped to the PHARE ontology using synonyms, entity descriptions and hierarchies of entities and roles. Once mapped, relationships can be normalized and compared using the structure of the ontology to identify relationships that have similar semantics but different syntax. We compare and contrast the manual procedure with a fully automated approach using WordNet to quantify the degree of integration enabled by iterative curation and refinement of the PHARE ontology. The result of such integration is a repository of normalized biomedical relationships, named PHARE-KB, which can be queried using Semantic Web technologies such as SPARQL and can be visualized in the form of a biological network.</p></sec><sec><title>Conclusions</title><p>The PHARE ontology serves as a common semantic framework to integrate more than 40,000 relationships pertinent to pharmacogenomics. The PHARE ontology forms the foundation of a knowledge base named PHARE-KB. Once populated with relationships, PHARE-KB (<italic>i</italic>) can be visualized in the form of a biological network to guide human tasks such as database curation and (<italic>ii</italic>) can be queried programmatically to guide bioinformatics applications such as the prediction of molecular interactions. PHARE is available at <ext-link ext-link-type="uri" xlink:href="http://purl.bioontology.org/ontology/PHARE">http://purl.bioontology.org/ontology/PHARE</ext-link>.</p></sec></abstract><conference><conf-date>9-10 July 2010</conf-date><conf-name>Bio-Ontologies 2010: Semantic Applications in Life Sciences</conf-name><conf-loc>Boston, MA, USA</conf-loc></conference></article-meta></front></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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