title: Relation mining experiments in the pharmacogenomics domain.
abstract: The mutual interactions among genes, diseases, and drugs are at the heart of biomedical research, and are especially important for the pharmacological industry. The recent trend towards personalized medicine makes it increasingly relevant to be able to tailor drugs to specific genetic makeups. The pharmacogenetics and pharmacogenomics knowledge base (PharmGKB) aims at capturing relevant information about such interactions from several sources, including curation of the biomedical literature. Advanced text mining tools which can support the process of manual curation are increasingly necessary in order to cope with the deluge of new published results. However, effective evaluation of those tools requires the availability of manually curated data as gold standard. In this paper we discuss how the existing PharmGKB database can be used for such an evaluation task in a way similar to the usage of gold standard data derived from protein-protein interaction databases in one of the recent BioCreative shared tasks. Additionally, we present our own considerations and results on the feasibility and difficulty of such a task.
authors.affiliation: Institute of Computational Linguistics, University of Zurich, Binzmühlestrasse 14, 8050 Zürich, Switzerland. fabio.rinaldi@uzh.ch
authors.forename: Fabio
authors.initials: F
authors.lastname: Rinaldi
authors.forename: Gerold
authors.initials: G
authors.lastname: Schneider
authors.forename: Simon
authors.initials: S
authors.lastname: Clematide
mesh_terms: D000043:Abstracting and Indexing; D000818:Animals; D019295:Computational Biology / Q000379:methods*; D057225:Data Mining / Q000379:methods*; D016208:Databases, Factual; D006801:Humans; D051188:Knowledge Bases; D010597:Pharmacogenetics / Q000379:methods*