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SR4GN: A Species Recognition Software Tool for Gene Normalization

Overview of attention for article published in PLOS ONE, June 2012
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Title
SR4GN: A Species Recognition Software Tool for Gene Normalization
Published in
PLOS ONE, June 2012
DOI 10.1371/journal.pone.0038460
Pubmed ID
Authors

Chih-Hsuan Wei, Hung-Yu Kao, Zhiyong Lu

Abstract

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.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 4%
Brazil 1 2%
Switzerland 1 2%
Spain 1 2%
South Africa 1 2%
Unknown 47 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 21%
Student > Master 10 19%
Researcher 9 17%
Student > Bachelor 6 11%
Student > Postgraduate 5 9%
Other 9 17%
Unknown 3 6%
Readers by discipline Count As %
Computer Science 23 43%
Agricultural and Biological Sciences 9 17%
Medicine and Dentistry 6 11%
Engineering 4 8%
Linguistics 2 4%
Other 7 13%
Unknown 2 4%