Herrero Zazo, MaríaHastings, JannaSegura-Bedmar, IsabelCroset, SamuelMartínez Fernández, PalomaSteinbeck, Christoph2015-04-232015-04-232014-01Semantic Web Applications and Tools for Life Sciences 1114 (2014), pp. 1-151613-0073https://hdl.handle.net/10016/20475Proceedings of: The 6th International Workshop on Semantic Web Applications and Tools for Life Sciences (SWAT4LS 2013). Took place 2013, December 11-12, in Edinburgh, UK. The evnt Web site http://www.swat4ls.org/workshops/edinburgh2013/Drug-drug interactions form a significant risk group for adverse effects associ-ated with pharmaceutical treatment. These interactions are often reported in the literature, however, they are sparsely represented in machine-readable re-sources, such as online databases, thesauri or ontologies. These knowledge sources play a pivotal role in Natural Language Processing (NLP) systems since they provide a knowledge representation about the world or a particular do-main. While ontologies for drugs and their effects have proliferated in recent years, there is no ontology capable of describing and categorizing drug-drug in-teractions. Moreover, there is no artifact that represents all the possible mecha-nisms that can lead to a DDI. To fill this gap we propose DINTO, an ontology for drug-drug interactions and their mechanisms. In this paper we describe the classes, relationships and overall structure of DINTO. The ontology is free for use and available at https://code.google.com/p/dinto/16application/pdfeng© AuthorsOntologyDrug-drug interactionsText miningSemanticsPharma-cologyconference paperInformáticaopen access115Semantic Web Applications and Tools for Life Sciences1114CC/0000021546