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.
Highlights
MicroRNAs are a class of 21-25nt non-coding RNAs that negatively regulate gene expression via complementary pairing to mRNA
MicroRNAs are an important class of RNAs that regulate a wide range of biological processes by post-transcriptional regulation of gene expression
The amount of literature describing experimentally validated miRNA targets is increasing rapidly, which poses a challenge to researchers and biocurators to stay up-to-date with the available information
Summary
MicroRNAs (miRNAs) are a class of 21-25nt non-coding RNAs that negatively regulate gene expression via complementary pairing to mRNA. MiRNAs have been found to regulate a wide range of cellular and development processes through gene expression suppression or mRNA degradation [2]. Identification of miRNA target genes is crucial for understanding the role of miRNA in various biological processes. Experimental validation of the predicted targets is necessary. Experimental validation methods include gene-specific techniques, e.g., reporter gene assays and assessment of miRNA and target mRNA co-expression [7], or high-throughput techniques. Validated miRNA targets are usually reported in the literature, and several databases have been built to store manually curated miRNA-target pairs, allowing researchers to access the latest results of experimentally validated miRNA targets.
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