CSmiRTar: Condition-Specific microRNA targets database

PLoS One. 2017 Jul 13;12(7):e0181231. doi: 10.1371/journal.pone.0181231. eCollection 2017.

Abstract

MicroRNAs (miRNAs) are functional RNA molecules which play important roles in the post-transcriptional regulation. miRNAs regulate their target genes by repressing translation or inducing degradation of the target genes' mRNAs. Many databases have been constructed to provide computationally predicted miRNA targets. However, they cannot provide the miRNA targets expressed in a specific tissue and related to a specific disease at the same time. Moreover, they cannot provide the common targets of multiple miRNAs and the common miRNAs of multiple genes at the same time. To solve these two problems, we construct a database called CSmiRTar (Condition-Specific miRNA Targets). CSmiRTar collects computationally predicted targets of 2588 human miRNAs and 1945 mouse miRNAs from four most widely used miRNA target prediction databases (miRDB, TargetScan, microRNA.org and DIANA-microT) and implements functional filters which allows users to search (i) a miRNA's targets expressed in a specific tissue or/and related to a specific disease, (ii) multiple miRNAs' common targets expressed in a specific tissue or/and related to a specific disease, (iii) a gene's miRNAs related to a specific disease, and (iv) multiple genes' common miRNAs related to a specific disease. We believe that CSmiRTar will be a useful database for biologists to study the molecular mechanisms of post-transcriptional regulation in human or mouse. CSmiRTar is available at http://cosbi.ee.ncku.edu.tw/CSmiRTar/ or http://cosbi4.ee.ncku.edu.tw/CSmiRTar/.

MeSH terms

  • Algorithms
  • Animals
  • Databases, Genetic*
  • Gene Expression Regulation*
  • Genetic Predisposition to Disease / genetics
  • Humans
  • Mice
  • MicroRNAs / genetics*
  • Organ Specificity / genetics
  • User-Computer Interface

Substances

  • MicroRNAs

Grants and funding

This work was supported by National Cheng Kung University and Ministry of Science and Technology of Taiwan [MOST-105-2221-E-006-203-MY2]. Funding for open access charge: National Cheng Kung University and Ministry of Science and Technology of Taiwan. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.