Mar 18, 2010

miRSel: automated extraction of associations between microRNAs and genes from the biomedical literature

BMC Bioinformatics
Haroon NaeemRalf Zimmer

Abstract

MicroRNAs have been discovered as important regulators of gene expression. To identify the target genes of microRNAs, several databases and prediction algorithms have been developed. Only few experimentally confirmed microRNA targets are available in databases. Many of the microRNA targets stored in databases were derived from large-scale experiments that are considered not very reliable. We propose to use text mining of publication abstracts for extracting microRNA-gene associations including microRNA-target relations to complement current repositories. The microRNA-gene association database miRSel combines text-mining results with existing databases and computational predictions. Text mining enables the reliable extraction of microRNA, gene and protein occurrences as well as their relationships from texts. Thereby, we increased the number of human, mouse and rat miRNA-gene associations by at least three-fold as compared to e.g. TarBase, a resource for miRNA-gene associations. Our database miRSel offers the currently largest collection of literature derived miRNA-gene associations. Comprehensive collections of miRNA-gene associations are important for the development of miRNA target prediction tools and the analysis of regulat...Continue Reading

  • References43
  • Citations33

References

  • References43
  • Citations33

Mentioned in this Paper

MLXIP gene
Twitter Messaging
Genome
Caenorhabditis elegans
Sequence Determinations, RNA
MIR21 wt Allele
MIR1224 gene
Candidate Disease Gene
Ncbi Taxonomy
RNA, Small Temporal

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