Paper: Automatic Approaches for Gene-Drug Interaction Extraction from Biomedical Text: Corpus and Comparative Evaluation

ACL ID W12-2427
Title Automatic Approaches for Gene-Drug Interaction Extraction from Biomedical Text: Corpus and Comparative Evaluation
Venue Workshop on Biomedical Natural Language Processing
Session
Year 2012
Authors

Publications that report genotype-drug inte- raction findings, as well as manually curated databases such as DrugBank and PharmGKB are essential to advancing pharmacogenomics, a relatively new area merging pharmacology and genomic research. Natural language processing (NLP) methods can be very useful for automatically extracting knowledge such as gene-drug interactions, offering researchers immediate access to published findings, and allowing curators a shortcut for their work. We present a corpus of gene-drug interac- tions for evaluating and training systems to extract those interactions. The corpus in- cludes 551 sentences that have a mention of a drug and a gene from about 600 journals found to be relevant to pharmacogenomics through an analysis of gene-drug relationsh...