miRTar: an integrated system for identifying miRNA-target interactions in human

Justin Bo-Kai Hsu, Chih Ming Chiu, Sheng Da Hsu, Wei Yun Huang, Chia-Hung Chien, Tzong-Yi Lee, Hsien-Da Huang

Research output: Contribution to journalArticlepeer-review

90 Scopus citations

Abstract

Background: MicroRNAs (miRNAs) are small non-coding RNA molecules that are similar to 22-nt-long sequences capable of suppressing protein synthesis. Previous research has suggested that miRNAs regulate 30% or more of the human protein-coding genes. The aim of this work is to consider various analyzing scenarios in the identification of miRNA-target interactions, as well as to provide an integrated system that will aid in facilitating investigation on the influence of miRNA targets by alternative splicing and the biological function of miRNAs in biological pathways.

Results: This work presents an integrated system, miRTar, which adopts various analyzing scenarios to identify putative miRNA target sites of the gene transcripts and elucidates the biological functions of miRNAs toward their targets in biological pathways. The system has three major features. First, the prediction system is able to consider various analyzing scenarios (1 miRNA: 1 gene, 1: N, N: 1, N: M, all miRNAs: N genes, and N miRNAs: genes involved in a pathway) to easily identify the regulatory relationships between interesting miRNAs and their targets, in 3'UTR, 5'UTR and coding regions. Second, miRTar can analyze and highlight a group of miRNA-regulated genes that participate in particular KEGG pathways to elucidate the biological roles of miRNAs in biological pathways. Third, miRTar can provide further information for elucidating the miRNA regulation, i.e., miRNA-target interactions, affected by alternative splicing.

Conclusions: In this work, we developed an integrated resource, miRTar, to enable biologists to easily identify the biological functions and regulatory relationships between a group of known/putative miRNAs and protein coding genes. miRTar is now available at http://miRTar.mbc.nctu.edu.tw/.
Original languageEnglish
JournalBMC Bioinformatics
Volume12
DOIs
StatePublished - 26 Jul 2011

Keywords

  • MICRORNA TARGETS; MESSENGER-RNAS; FUNCTIONAL ANNOTATION; LET-7 MICRORNA; BINDING-SITES; GENOMIC MAPS; WEB TOOL; DATABASE; PREDICTION; GENES

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