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BioMed Research International
Volume 2015, Article ID 918710, 7 pages
http://dx.doi.org/10.1155/2015/918710
Research Article

GNormPlus: An Integrative Approach for Tagging Genes, Gene Families, and Protein Domains

1National Center for Biotechnology Information (NCBI), 8600 Rockville Pike, Bethesda, MD 20894, USA
2Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 701, Taiwan

Received 15 January 2015; Revised 3 April 2015; Accepted 4 April 2015

Academic Editor: Yudong Cai

Copyright © 2015 Chih-Hsuan Wei et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The automatic recognition of gene names and their associated database identifiers from biomedical text has been widely studied in recent years, as these tasks play an important role in many downstream text-mining applications. Despite significant previous research, only a small number of tools are publicly available and these tools are typically restricted to detecting only mention level gene names or only document level gene identifiers. In this work, we report GNormPlus: an end-to-end and open source system that handles both gene mention and identifier detection. We created a new corpus of 694 PubMed articles to support our development of GNormPlus, containing manual annotations for not only gene names and their identifiers, but also closely related concepts useful for gene name disambiguation, such as gene families and protein domains. GNormPlus integrates several advanced text-mining techniques, including SimConcept for resolving composite gene names. As a result, GNormPlus compares favorably to other state-of-the-art methods when evaluated on two widely used public benchmarking datasets, achieving 86.7% F1-score on the BioCreative II Gene Normalization task dataset and 50.1% F1-score on the BioCreative III Gene Normalization task dataset. The GNormPlus source code and its annotated corpus are freely available, and the results of applying GNormPlus to the entire PubMed are freely accessible through our web-based tool PubTator.