miRTex: A Text Mining System for miRNAGene Relation Extraction
Date
2015-09-25
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Publisher
PLOS (Public Library of Science)
Abstract
MicroRNAs (miRNAs) regulate a wide range of cellular and developmental processes
through gene expression suppression or mRNA degradation. Experimentally validated
miRNA gene targets are often reported in the literature. In this paper, we describe miRTex,
a text mining system that extracts miRNA-target relations, as well as miRNA-gene and
gene-miRNA regulation relations. The system achieves good precision and recall when
evaluated on a literature corpus of 150 abstracts with F-scores close to 0.90 on the three different
types of relations. We conducted full-scale text mining using miRTex to process all
the Medline abstracts and all the full-length articles in the PubMed Central Open Access
Subset. The results for all the Medline abstracts are stored in a database for interactive
query and file download via the website at http://proteininformationresource.org/mirtex.
Using miRTex, we identified genes potentially regulated by miRNAs in Triple Negative
Breast Cancer, as well as miRNA-gene relations that, in conjunction with kinase-substrate
relations, regulate the response to abiotic stress in Arabidopsis thaliana. These two use
cases demonstrate the usefulness of miRTex text mining in the analysis of miRNA-regulated
biological processes.
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Citation
Li G, Ross KE, Arighi CN, Peng Y, Wu CH, Vijay-Shanker K (2015) miRTex: A Text Mining System for miRNA-Gene Relation Extraction. PLoS Comput Biol 11(9): e1004391. doi:10.1371/journal. pcbi.1004391