SR4GN: a species recognition software tool for gene normalization.
As suggested in recent studies, species recognition and disambiguation is one of the most critical and challenging steps in many downstream text-mining applications such as the gene normalization task and protein-protein interaction extraction. We report SR4GN: an open source tool for species recognition and disambiguation in biomedical text. In addition to the species detection function in existing tools, SR4GN is optimized for the Gene Normalization task. As such it is developed to link detected species with corresponding gene mentions in a document. SR4GN achieves 85.42% in accuracy and compares favorably to the other state-of-the-art techniques in benchmark experiments. Finally, SR4GN is implemented as a standalone software tool, thus making it convenient and robust for use in many text-mining applications. SR4GN can be downloaded at: http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/downloads/SR4GN.
National Center for Biotechnology Information, National Library of Medicine, Bethesda, Maryland, United States of America.
Chih-Hsuan
CH
Wei
Hung-Yu
HY
Kao
Zhiyong
Z
Lu
D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D057225:Data Mining; D012984:Software