Literature DB >> 15360854

Drug interaction ontology (DIO) for inferences of possible drug-drug interactions.

Sumi Yoshikawa1, Kenji Satou, Akihiko Konagaya.   

Abstract

Drug Interaction Ontology (DIO) was developed for formal representation of pharmacological knowledge. It provides a fundamental framework for accumulation of reusable knowledge components in molecular pharmacology. Ontology was employed and implemented as a relational model. Some features include: 1) Drug-biomolecule interaction was assumed as a primitive knowledge element. 2) Symbolic representation was developed for drug-biomolecule interaction. Consequences of two conjugated units of interaction were defined by using symbols. These are applied for query development for identification of possible drug-drug interaction. 3) The triadic relationship model was developed as a ground model for bio-logical interactions and/or function, including semantic ones. One application of DIO is to support hypothesis generation of drug interaction by providing new hypotheses from a structured database storing literature information on known drug-biomolecule interactions. A knowledge base using DIO that contains information beginning with anti-cancer drugs is now under development. Detection of possible drug interaction was tested and its capacity to lead clinically known ones was confirmed. The system generated theoretically possible drug-drug interactions, which implies potential usefulness of new drugs to be tested before actual clinical application. In this paper, sorivudine and 5-fluorouracil mediated by dihydropyrimidine dehydrogenase are presented.

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Year:  2004        PMID: 15360854

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  5 in total

1.  PLIO: an ontology for formal description of protein-ligand interactions.

Authors:  Olga Ivchenko; Erfan Younesi; Mohammad Shahid; Antje Wolf; Bernd Müller; Martin Hofmann-Apitius
Journal:  Bioinformatics       Date:  2011-05-05       Impact factor: 6.937

2.  Drug-drug interaction discovery and demystification using Semantic Web technologies.

Authors:  Adeeb Noor; Abdullah Assiri; Serkan Ayvaz; Connor Clark; Michel Dumontier
Journal:  J Am Med Inform Assoc       Date:  2017-05-01       Impact factor: 4.497

3.  PDON: Parkinson's disease ontology for representation and modeling of the Parkinson's disease knowledge domain.

Authors:  Erfan Younesi; Ashutosh Malhotra; Michaela Gündel; Phil Scordis; Alpha Tom Kodamullil; Matt Page; Bernd Müller; Stephan Springstubbe; Ullrich Wüllner; Dieter Scheller; Martin Hofmann-Apitius
Journal:  Theor Biol Med Model       Date:  2015-09-22       Impact factor: 2.432

Review 4.  Standard Lexicons, Coding Systems and Ontologies for Interoperability and Semantic Computation in Imaging.

Authors:  Kenneth C Wang
Journal:  J Digit Imaging       Date:  2018-06       Impact factor: 4.056

5.  Drug interaction prediction using ontology-driven hypothetical assertion framework for pathway generation followed by numerical simulation.

Authors:  Takeshi Arikuma; Sumi Yoshikawa; Ryuzo Azuma; Kentaro Watanabe; Kazumi Matsumura; Akihiko Konagaya
Journal:  BMC Bioinformatics       Date:  2008-05-28       Impact factor: 3.169

  5 in total

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