DINTO is an OWL ontology that systematically organizes all drug-drug interaction (DDI) related information.
Drug-drug interactions (DDIs) form a significant risk group for adverse effects associated with pharmaceutical treatment. These interactions are often reported in the literature, however, they are sparsely represented in machine-readable resources, such as online databases, thesauri or ontologies. DINTO is an ontology that describes and categorizes DDIs and all the possible mechanisms that can lead to them (including both pharmacodynamic and pharmacokinetic DDI mechanisms).
DINTO is updated and can be downloaded from https://github.com/labda/DINTO/
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Please cite the following reference when using this corpus:
Herrero-Zazo, María; Segura-Bedmar, Isabel; Hastings, Janna; Martínez, Paloma (2015). DINTO: Using OWL ontologies and SWRL rules to infer drug-drug interactions and their mechanisms. Journal of Chemical Information and Modeling. Just Accepted Manuscript.DOI: 10.1021/acs.jcim.5b00119
For more information, a detailed description of DINTO, the methodology followed for its construction and evaluation, and the different application scenarios where it has been used can be found in the PhD Dissertation http://labda.inf.uc3m.es/doku.php?id=es:labda_asignacion_tesis/ Semantic Resources in Pharmacovigilance: a Corpus and an Ontology for Drug-Drug Interactions (2015). Herrero-Zazo, María. Universidad Carlos III de Madrid.
This ontology has been created by the at University Carlos III of Madrid in collaboration with the ChEBI ontology team.
Contact address: email@example.com