ArticleBMC bioinformatics2019
PGxO and PGxLOD: a reconciliation of pharmacogenomic knowledge of various provenances, enabling further comparison.
Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Pharmacogenomics Tools for Precision Public Health and Lessons for Low- and Middle-Income Countries: A Scoping Review.Pharmacogenomics and personalized medicine · 2025Review
- Provenance Information for Biomedical Data and Workflows: Scoping Review.Journal of medical Internet research · 2024Article
- Toxicology knowledge graph for structural birth defects.Communications medicine · 2023Article
- Leveraging a pharmacogenomics knowledgebase to formulate a drug response phenotype terminology for genomic medicine.Bioinformatics (Oxford, England) · 2022Article
- PharmGKB, an Integrated Resource of Pharmacogenomic Knowledge.Current protocols · 2021Article
- Investigating ADR mechanisms with Explainable AI: a feasibility study with knowledge graph mining.BMC medical informatics and decision making · 2021Article
- PGxCorpus, a manually annotated corpus for pharmacogenomics.Scientific data · 2020Article
- The 2017 Network Tools and Applications in Biology (NETTAB) workshop: aims, topics and outcomes.BMC bioinformatics · 2019Article
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8 authors.
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Abstract
backgroundPharmacogenomics (PGx) studies how genomic variations impact variations in drug response phenotypes. Knowledge in pharmacogenomics is typically composed of units that have the form of ternary relationships gene variant - drug - adverse event. Such a relationship states that an adverse event may occur for patients having the specified gene variant and being exposed to the specified drug. State-of-the-art knowledge in PGx is mainly available in reference databases such as PharmGKB and reported in scientific biomedical literature. But, PGx knowledge can also be discovered from clinical data, such as Electronic Health Records (EHRs), and in this case, may either correspond to new knowledge or confirm state-of-the-art knowledge that lacks "clinical counterpart" or validation. For this reason, there is a need for automatic comparison of knowledge units from distinct sources.
resultsIn this article, we propose an approach, based on Semantic Web technologies, to represent and compare PGx knowledge units. To this end, we developed PGxO, a simple ontology that represents PGx knowledge units and their components. Combined with PROV-O, an ontology developed by the W3C to represent provenance information, PGxO enables encoding and associating provenance information to PGx relationships. Additionally, we introduce a set of rules to reconcile PGx knowledge, i.e. to identify when two relationships, potentially expressed using different vocabularies and levels of granularity, refer to the same, or to different knowledge units. We evaluated our ontology and rules by populating PGxO with knowledge units extracted from PharmGKB (2701), the literature (65,720) and from discoveries reported in EHR analysis studies (only 10, manually extracted); and by testing their similarity. We called PGxLOD (PGx Linked Open Data) the resulting knowledge base that represents and reconciles knowledge units of those various origins.
conclusionsThe proposed ontology and reconciliation rules constitute a first step toward a more complete framework for knowledge comparison in PGx. In this direction, the experimental instantiation of PGxO, named PGxLOD, illustrates the ability and difficulties of reconciling various existing knowledge sources.
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