PmiRtarbase: A positive miRNA-target regulations database

Peng Xu, Xianbin Li, Yijun Liang, Zhenshen Bao*, Fengyue Zhang, Lili Gu, Saeed Kosari, Wenbin Liu

*Corresponding author for this work

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Abstract

MicroRNAs (miRNAs) are ~22 nt small non-coding RNA segments that are widely involved in the regulation of gene expression. Accumulating evidences show that miRNAs not only inhibit the expression of some targeted genes but also promote that of some targeted genes in specific conditions. Over the past decades, many miRNA-target databases have been developed from computational prediction and/or experimental validation perspectives. However, there is no database available to systematically collect positive miRNA-target associations that are essential in deciphering the miRNA regulation mechanism. To promote the miRNA study, we developed a new database: PmiRtarbase that acquires validated positive miRNA-target interactions by mining published literature. It includes 312 curated associations between 119 miRNAs and 169 genes in 8 species from 130 studies and summarizes the conditions and detailed descriptions of the miRNA-target associations. We also constructed a database named PmiRtarbase, a user-friendly interface to conveniently search and download all related entries. This elaborate database aims to serve as a beneficial resource for studying the miRNA positive regulation mechanism and miRNA-based therapeutics. Data availability: The full positive miRNA-target data can be accessed through the link http://www.lwb-lab.cn/PmiRtarbase. Users of this dataset should acknowledge the contributions of the original authors and properly cite this article.

Original languageEnglish
Article number107690
JournalComputational Biology and Chemistry
Volume98
DOIs
Publication statusPublished - Jun 2022
Externally publishedYes

Keywords

  • MiRNA
  • PmiRtarbase
  • Positive miRNA-target interaction

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Xu, P., Li, X., Liang, Y., Bao, Z., Zhang, F., Gu, L., Kosari, S., & Liu, W. (2022). PmiRtarbase: A positive miRNA-target regulations database. Computational Biology and Chemistry, 98, Article 107690. https://doi.org/10.1016/j.compbiolchem.2022.107690