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dc.contributor.authorKulmanov, Maxat
dc.contributor.authorSmaili, Fatima Z.
dc.contributor.authorGao, Xin
dc.contributor.authorHoehndorf, Robert
dc.date.accessioned2020-10-18T12:36:49Z
dc.date.available2020-10-18T12:36:49Z
dc.date.issued2020-10-13
dc.date.submitted2020-05-07
dc.identifier.citationKulmanov, M., Smaili, F. Z., Gao, X., & Hoehndorf, R. (2020). Semantic similarity and machine learning with ontologies. Briefings in Bioinformatics. doi:10.1093/bib/bbaa199
dc.identifier.issn1467-5463
dc.identifier.pmid33049044
dc.identifier.doi10.1093/bib/bbaa199
dc.identifier.urihttp://hdl.handle.net/10754/665622
dc.description.abstractOntologies have long been employed in the life sciences to formally represent and reason over domain knowledge and they are employed in almost every major biological database. Recently, ontologies are increasingly being used to provide background knowledge in similarity-based analysis and machine learning models. The methods employed to combine ontologies and machine learning are still novel and actively being developed. We provide an overview over the methods that use ontologies to compute similarity and incorporate them in machine learning methods; in particular, we outline how semantic similarity measures and ontology embeddings can exploit the background knowledge in ontologies and how ontologies can provide constraints that improve machine learning models. The methods and experiments we describe are available as a set of executable notebooks, and we also provide a set of slides and additional resources at https://github.com/bio-ontology-research-group/machine-learning-with-ontologies.
dc.description.sponsorshipThis work was supported by funding from King Abdullah University of Science and Technology, Office of Sponsored Research under award no. URF/1/3454-01-01, URF/1/3790-01-01, FCC/1/1976-04, FCC/1/1976-06, FCC/1/1976-17, FCC/1/19-76-18, FCC/1/1976-23, FCC/1/1976-25, FCC/1/1976-26 and URF/1/3450-01.
dc.publisherOxford University Press (OUP)
dc.relation.urlhttps://academic.oup.com/bib/advance-article/doi/10.1093/bib/bbaa199/5922325
dc.rightsThis is an Open Access article distributed under the terms of the Creative Commons Attribution License ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titleSemantic similarity and machine learning with ontologies.
dc.typeArticle
dc.contributor.departmentBio-Ontology Research Group (BORG)
dc.contributor.departmentComputational Bioscience Research Center (CBRC)
dc.contributor.departmentComputer Science Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentStructural and Functional Bioinformatics Group
dc.identifier.journalBriefings in bioinformatics
dc.eprint.versionPublisher's Version/PDF
kaust.personKulmanov, Maxat
kaust.personSmaili, Fatima Zohra
kaust.personGao, Xin
kaust.personHoehndorf, Robert
kaust.grant.numberURF/1/3454-01-01
kaust.grant.numberURF/1/3790-01-01
kaust.grant.numberFCC/1/1976-04
kaust.grant.numberFCC/1/1976-06
kaust.grant.numberFCC/1/1976-17
kaust.grant.numberFCC/1/19-76-18
kaust.grant.numberFCC/1/1976-23
kaust.grant.numberFCC/1/1976-25
kaust.grant.numberFCC/1/1976-26
kaust.grant.numberURF/1/3450-01.
dc.date.accepted2020-08-03
refterms.dateFOA2020-10-18T12:37:17Z
kaust.acknowledged.supportUnitOSR
dc.date.published-online2020-10-13
dc.date.published-print2021-07-20


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This is an Open Access article distributed under the terms of the Creative Commons Attribution License ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Except where otherwise noted, this item's license is described as This is an Open Access article distributed under the terms of the Creative Commons Attribution License ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.