PGxO: A very lite ontology to reconcile pharmacogenomic knowledge units

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1 LORIA (CNRS, Inria Nancy-Grand Est, Université de Lorraine), Vandoeuvre-lès-Nancy, France
2 LIRMM (CNRS, Université de Montpellier), Montpellier, France
3 BMIR (Stanford University), Stanford, USA
DOI
10.7287/peerj.preprints.3140v1
Published
Accepted
Subject Areas
Bioinformatics, Artificial Intelligence, Data Mining and Machine Learning, Databases, World Wide Web and Web Science
Keywords
ontology, knowledge engineering, pharmacogenomics, knowledge representation, semantic web, knowledge comparison
Copyright
© 2017 Monnin et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
Cite this article
Monnin P, Jonquet C, Legrand J, Napoli A, Coulet A. 2017. PGxO: A very lite ontology to reconcile pharmacogenomic knowledge units. PeerJ Preprints 5:e3140v1

Abstract

We present in this article a lightweight ontology named PGxO and a set of rules for its instantiation, which we developed as a frame for reconciling and tracing pharmacogenomics (PGx) knowledge. PGx studies how genomic variations impact variations in drug response phenotypes. Knowledge in PGx is typically composed of units that have the form of ternary relationships gene variant–drug–adverse event, stating that an adverse event may occur for patients having the gene variant when being exposed to the drug. These knowledge units (i) are available in reference databases, such as PharmGKB, are reported in the scientific biomedical literature and (ii) may be discovered by mining clinical data such as Electronic Health Records (EHRs). Therefore, knowledge in PGx is heterogeneously described (i.e., with various quality, granularity, vocabulary, etc.). It is consequently worth to extract, then compare, assertions from distinct resources. Using PGxO, one can represent multiple provenances for pharmacogenomic knowledge units, and reconcile duplicates when they come from distinct sources.

Author Comment

This is an abstract which has been accepted for the NETTAB 2017 Workshop.