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Assisting manual literature curation for protein-protein interactions using BioQRator
Dongseop Kwon1, Sun Kim2, Soo-Yong Shin3
1Department of Computer Engineering, Myongji University, Yongin 449-728, South Korea, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA, Department of Biomedical Informatics, Asan Medical Center, Seoul 138-736, South Korea and Institute for Research in Immunology and Cancer, Université de Montréal, Montréal QC H3C 3J7, Canada dongseop@mju.ac.kr.
Abstract:
The time-consuming nature of manual curation and the rapid growth of biomedical literature severely limit the number of articles that database curators can scrutinize and annotate. Hence, semi-automatic tools can be a valid support to increase annotation throughput. Although a handful of curation assistant tools are already available, to date, little has been done to formally evaluate their benefit to biocuration. Moreover, most curation tools are designed for specific problems. Thus, it is not easy to apply an annotation tool for multiple tasks. BioQRator is a publicly available web-based tool for annotating biomedical literature. It was designed to support general tasks, i.e. any task annotating entities and relationships. In the BioCreative IV edition, BioQRator was tailored for protein- protein interaction (PPI) annotation by migrating information from PIE the search. The results obtained from six curators showed that the precision on the top 10 documents doubled with PIE the search compared with PubMed search results. It was also observed that the annotation time for a full PPI annotation task decreased for a beginner-intermediate level annotator. This finding is encouraging because text-mining techniques were not directly involved in the full annotation task and BioQRator can be easily integrated with any text-mining resources. Database URL: http://www.bioqrator.org/.
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