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dc.contributor.authorRodríguez-García, MÁen
dc.contributor.authorGkoutos, GVen
dc.contributor.authorSchofield, Paulen
dc.contributor.authorHoehndorf, Ren
dc.date.accessioned2019-02-16T00:31:00Z
dc.date.available2019-02-16T00:31:00Z
dc.date.issued2017-12-19en
dc.identifier.issn1613-0073
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/289514
dc.description.abstract© 2017 The Author(s). Background: Integration and analysis of phenotype data from humans and model organisms is a key challenge in building our understanding of normal biology and pathophysiology. However, the range of phenotypes and anatomical details being captured in clinical and model organism databases presents complex problems when attempting to match classes across species and across phenotypes as diverse as behaviour and neoplasia. We have previously developed PhenomeNET, a system for disease gene prioritization that includes as one of its components an ontology designed to integrate phenotype ontologies. While not applicable to matching arbitrary ontologies, PhenomeNET can be used to identify related phenotypes in different species, including human, mouse, zebrafish, nematode worm, fruit fly, and yeast. Results: Here, we apply the PhenomeNET to identify related classes from two phenotype and two disease ontologies using automated reasoning. We demonstrate that we can identify a large number of mappings, some of which require automated reasoning and cannot easily be identified through lexical approaches alone. Combining automated reasoning with lexical matching further improves results in aligning ontologies. Conclusions: PhenomeNET can be used to align and integrate phenotype ontologies. The results can be utilized for biomedical analyses in which phenomena observed in model organisms are used to identify causative genes and mutations underlying human disease.
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleIntegrating phenotype ontologies with PhenomeNETen
dc.typeArticle
prism.issueIdentifier1en
prism.publicationDate2017en
prism.publicationNameJournal of Biomedical Semanticsen
prism.volume8en
dc.identifier.doi10.17863/CAM.36764
dcterms.dateAccepted2017-11-22en
rioxxterms.versionofrecord10.1186/s13326-017-0167-4en
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2017-12-19en
dc.contributor.orcidSchofield, Paul [0000-0002-5111-7263]
dc.identifier.eissn2041-1480
rioxxterms.typeJournal Article/Reviewen


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International