PGxCorpus, a manually annotated corpus for pharmacogenomics.
Fiche publication
Date publication
janvier 2020
Journal
Scientific data
Auteurs
Membres identifiés du Cancéropôle Est :
Dr DEVIGNES Marie-Dominique
Tous les auteurs :
Legrand J, Gogdemir R, Bousquet C, Dalleau K, Devignes MD, Digan W, Lee CJ, Ndiaye NC, Petitpain N, Ringot P, Smaïl-Tabbone M, Toussaint Y, Coulet A
Lien Pubmed
Résumé
Pharmacogenomics (PGx) studies how individual gene variations impact drug response phenotypes, which makes PGx-related knowledge a key component towards precision medicine. A significant part of the state-of-the-art knowledge in PGx is accumulated in scientific publications, where it is hardly reusable by humans or software. Natural language processing techniques have been developed to guide experts who curate this amount of knowledge. But existing works are limited by the absence of a high quality annotated corpus focusing on PGx domain. In particular, this absence restricts the use of supervised machine learning. This article introduces PGxCorpus, a manually annotated corpus, designed to fill this gap and to enable the automatic extraction of PGx relationships from text. It comprises 945 sentences from 911 PubMed abstracts, annotated with PGx entities of interest (mainly gene variations, genes, drugs and phenotypes), and relationships between those. In this article, we present the corpus itself, its construction and a baseline experiment that illustrates how it may be leveraged to synthesize and summarize PGx knowledge.
Référence
Sci Data. 2020 Jan 2;7(1):3