title: DINTO: Using OWL Ontologies and SWRL Rules to Infer Drug-Drug Interactions and Their Mechanisms.
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. The ontology is available from https://code.google.com/p/dinto/.
authors.affiliation: Department of Computer Science, Universidad Carlos III de Madrid , Leganés 28911, Madrid, Spain.
authors.forename: María
authors.initials: M
authors.lastname: Herrero-Zazo
authors.affiliation: Department of Computer Science, Universidad Carlos III de Madrid , Leganés 28911, Madrid, Spain.
authors.forename: Isabel
authors.initials: I
authors.lastname: Segura-Bedmar
authors.affiliation: Cheminformatics and Metabolism, European Bioinformatics Institute (EMBL-EBI) , Hinxton, CB10 1SD, U.K.
authors.forename: Janna
authors.initials: J
authors.lastname: Hastings
authors.affiliation: Department of Computer Science, Universidad Carlos III de Madrid , Leganés 28911, Madrid, Spain.
authors.forename: Paloma
authors.initials: P
authors.lastname: Martínez
mesh_terms: D062313:Databases, Pharmaceutical; D004347:Drug Interactions; D006801:Humans; D020407:Internet; D012660:Semantics; D012984:Software