DINTO: Using OWL ontologies and SWRL rules to infer drug-drug interactions and their mechanisms

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dc.contributor.author Herrero Zazo, María
dc.contributor.author Segura-Bedmar, Isabel
dc.contributor.author Hastings, Janna
dc.contributor.author Martínez Fernández, Paloma
dc.date.accessioned 2021-02-10T10:18:55Z
dc.date.available 2021-02-10T10:18:55Z
dc.date.issued 2015-08-01
dc.identifier.bibliographicCitation J. Chem. Inf. Model. 2015, 55, 8, 1698–1707
dc.identifier.issn 1549-9596
dc.identifier.uri http://hdl.handle.net/10016/31894
dc.description.abstract The early detection of drug drug interactions (DDIs) is limited by the diffuse spread of DDI information in heterogeneous sources. Computational methods promise to play a key role in the identification and explanation of DDIs on a large scale. However, such methods rely on the availability of computable representations describing the relevant domain knowledge. Current modeling efforts have focused on partial and shallow representations of the DDI domain, failing to adequately support computational inference and discovery applications. In this paper, we describe a comprehensive ontology for DDI knowledge (DINTO), which is the first formal representation of different types of DDIs and their mechanisms and its application in the prediction of DDIs. This project has been developed using currently available semantic web technologies, standards, and tools, and we have demonstrated that the combination of drug-related facts in DINTO and Semantic Web Rule Language (SWRL) rules can be used to infer DDIs and their different mechanisms on a large scale.<
dc.description.sponsorship This work was supported by the European Commission Seventh Framework Programme under the TrendMiner project [FP7-ICT287863].
dc.language.iso eng
dc.publisher ACS Publications
dc.rights Copyright © 2015, American Chemical Society
dc.subject.other Pharmacokinetics
dc.subject.other Pharmaceuticals
dc.subject.other Metabolism
dc.subject.other Peptides and proteins
dc.subject.other Mathematical methods
dc.title DINTO: Using OWL ontologies and SWRL rules to infer drug-drug interactions and their mechanisms
dc.type article
dc.subject.eciencia Informática
dc.identifier.doi https://doi.org/10.1021/acs.jcim.5b00119
dc.rights.accessRights openAccess
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/ICT287863
dc.type.version acceptedVersion
dc.identifier.publicationfirstpage 1698
dc.identifier.publicationissue 8
dc.identifier.publicationlastpage 1707
dc.identifier.publicationtitle Journal of Chemical Information and Modeling
dc.identifier.publicationvolume 55
dc.identifier.uxxi AR/0000017239
dc.contributor.funder European Commission
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