| URL: | http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/Demo/PubTator/ |
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| Description: | PubTator is a Web-based tool for accelerating manual literature curation (e.g. annotating biological entities and their relationships) through the use of advanced text-mining techniques. As an all-in-one system, PubTator provides one-stop service for annotating PubMed citations. We keep in sync with PubMed and update automatic computer annotations every day. |
| Year founded: | 2012 |
| Last update: | 2013-07-01 |
| Version: | V1.0 |
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Accessible
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| Country/Region: | United States |
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| University/Institution: | National Center for Biotechnology Information |
| Address: | 8600 Rockville Pike, Bethesda, Maryland, 20894 USA |
| City: | Bethesda |
| Province/State: | Maryland |
| Country/Region: | United States |
| Contact name (PI/Team): | Zhiyong Lu |
| Contact email (PI/Helpdesk): | zhiyong.lu@nih.gov |
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PubTator: a web-based text mining tool for assisting biocuration. [PMID: 23703206]
Manually curating knowledge from biomedical literature into structured databases is highly expensive and time-consuming, making it difficult to keep pace with the rapid growth of the literature. There is therefore a pressing need to assist biocuration with automated text mining tools. Here, we describe PubTator, a web-based system for assisting biocuration. PubTator is different from the few existing tools by featuring a PubMed-like interface, which many biocurators find familiar, and being equipped with multiple challenge-winning text mining algorithms to ensure the quality of its automatic results. Through a formal evaluation with two external user groups, PubTator was shown to be capable of improving both the efficiency and accuracy of manual curation. PubTator is publicly available at http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/Demo/PubTator/. |
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Accelerating literature curation with text-mining tools: a case study of using PubTator to curate genes in PubMed abstracts. [PMID: 23160414]
Today's biomedical research has become heavily dependent on access to the biological knowledge encoded in expert curated biological databases. As the volume of biological literature grows rapidly, it becomes increasingly difficult for biocurators to keep up with the literature because manual curation is an expensive and time-consuming endeavour. Past research has suggested that computer-assisted curation can improve efficiency, but few text-mining systems have been formally evaluated in this regard. Through participation in the interactive text-mining track of the BioCreative 2012 workshop, we developed PubTator, a PubMed-like system that assists with two specific human curation tasks: document triage and bioconcept annotation. On the basis of evaluation results from two external user groups, we find that the accuracy of PubTator-assisted curation is comparable with that of manual curation and that PubTator can significantly increase human curatorial speed. These encouraging findings warrant further investigation with a larger number of publications to be annotated. Database URL: http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/Demo/PubTator/ |