Title | BioCreative VI Precision Medicine Track: creating a training corpus for mining protein-protein interactions affected by mutations |
Publication Type | Conference Proceedings |
Year of Conference | 2017 |
Authors | Doğan RIslamaj, Chatr-aryamontri A, Kim S, Wei C-H, Peng Y, Comeau D, Lu Z |
Conference Name | BioNLP 2017 |
Pagination | 171–175 |
Date Published | 2017 |
Publisher | Association for Computational Linguistics |
Conference Location | Vancouver, Canada |
Abstract | The Precision Medicine Track in BioCre-ative VI aims to bring together the Bi-oNLP community for a novel challenge focused on mining the biomedical litera-ture in search of mutations and protein-protein interactions (PPI). In order to support this track with an effective train-ing dataset with limited curator time, the track organizers carefully reviewed Pub-Med articles from two different sources: curated public PPI databases, and the re-sults of state-of-the-art public text mining tools. We detail here the data collection, manual review and annotation process and describe this training corpus charac-teristics. We also describe a corpus per-formance baseline. This analysis will provide useful information to developers and researchers for comparing and devel-oping innovative text mining approaches for the BioCreative VI challenge and other Precision Medicine related applica-tions. |
DOI | 10.18653/v1/W17-2321 |