miReg: a resource for microRNA regulation

Author:

Barh Debmalya,Bhat Dattatraya,Viero Cedric

Abstract

SummaryMicroRNAs (miRNAs/miRs) are important cellular components that regulate gene expression at posttranscriptional level. Various upstream components regulate miR expression and any deregulation causes disease conditions. Therefore, understanding of miR regulatory network both at upstream and downstream level is crucial and a resource on this aspect will be helpful. Currently available miR databases are mostly related to downstream targets, sequences, or diseases. But as of now, no database is available that provides a complete picture of miR regulation in a specific condition.Our miR regulation web resource (miReg) is a manually curated one that represents validated upstream regulators (transcription factor, drug, physical, and chemical) along with downstream targets, associated biological process, experimental condition or disease state, up or down regulation of the miR in that condition, and corresponding PubMed references in a graphical and user friendly manner, browseable through 5 browsing options. We have presented exact facts that have been described in the corresponding literature in relation to a given miR, whether it’s a feed-back/feed-forward loop or inhibition/activation. Moreover we have given various links to integrate data and to get a complete picture on any miR listed. Current version (Version 1.0) of miReg contains 47 important human miRs with 295 relations using 190 absolute references. We have also provided an example on usefulness of miReg to establish signalling pathways involved in cardiomyopathy. We believe that miReg will be an essential miRNA knowledge base to research community, with its continuous upgrade and data enrichment.This HTML based miReg can be accessed from: www.iioab-mireg.webs.com or www.iioab.webs.com/mireg.htm.

Publisher

Walter de Gruyter GmbH

Subject

General Medicine

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. MicroRNA Bioinformatics;MicroRNA in Regenerative Medicine;2023

2. Predicting potential miRNA-disease associations by combining gradient boosting decision tree with logistic regression;Computational Biology and Chemistry;2020-04

3. Noncoding RNAs Databases: Current Status and Trends;Computational Biology of Non-Coding RNA;2019

4. Prediction of Non-coding RNAs as Drug Targets;Advances in Experimental Medicine and Biology;2018

5. MicroRNAs and complex diseases: from experimental results to computational models;Briefings in Bioinformatics;2017-10-17

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