Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/143374
Title: | ncRNA2MetS : a manually curated database for non-coding RNAs associated with metabolic syndrome | Authors: | Yao, Dengju Zhan, Xiaojuan Zhan, Xiaorong Kwoh, Chee Keong Sun, Yuezhongyi |
Keywords: | Engineering::Computer science and engineering | Issue Date: | 2019 | Source: | Yao, D., Zhan, X., Zhan, X., Kwoh, C. K., & Sun, Y. (2019). ncRNA2MetS : a manually curated database for non-coding RNAs associated with metabolic syndrome. PeerJ, 7(10), e7909-. doi:10.7717/peerj.7909 | Journal: | PeerJ | Abstract: | Metabolic syndrome is a cluster of the most dangerous heart attack risk factors (diabetes and raised fasting plasma glucose, abdominal obesity, high cholesterol and high blood pressure), and has become a major global threat to human health. A number of studies have demonstrated that hundreds of non-coding RNAs, including miRNAs and lncRNAs, are involved in metabolic syndrome-related diseases such as obesity, type 2 diabetes mellitus, hypertension, etc. However, these research results are distributed in a large number of literature, which is not conducive to analysis and use. There is an urgent need to integrate these relationship data between metabolic syndrome and non-coding RNA into a specialized database. To address this need, we developed a metabolic syndrome-associated non-coding RNA database (ncRNA2MetS) to curate the associations between metabolic syndrome and non-coding RNA. Currently, ncRNA2MetS contains 1,068 associations between five metabolic syndrome traits and 627 non-coding RNAs (543 miRNAs and 84 lncRNAs) in four species. Each record in ncRNA2MetS database represents a pair of disease-miRNA (lncRNA) association consisting of non-coding RNA category, miRNA (lncRNA) name, name of metabolic syndrome trait, expressive patterns of non-coding RNA, method for validation, specie involved, a brief introduction to the association, the article referenced, etc. We also developed a user-friendly website so that users can easily access and download all data. In short, ncRNA2MetS is a complete and high-quality data resource for exploring the role of non-coding RNA in the pathogenesis of metabolic syndrome and seeking new treatment options. The website is freely available at http://www.biomed-bigdata.com:50020/index.html. | URI: | https://hdl.handle.net/10356/143374 | ISSN: | 2167-8359 | DOI: | 10.7717/peerj.7909 | Schools: | School of Computer Science and Engineering | Rights: | © 2019 Yang et al. Distributed under Creative Commons CC-BY 4.0 | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | SCSE Journal Articles |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
ncRNA2MetS a manually curated database for non-coding RNAs associated with metabolic syndrome.pdf | 2.93 MB | Adobe PDF | ![]() View/Open |
SCOPUSTM
Citations
50
2
Updated on Mar 23, 2025
Web of ScienceTM
Citations
50
2
Updated on Oct 31, 2023
Page view(s)
274
Updated on Mar 24, 2025
Download(s) 50
106
Updated on Mar 24, 2025
Google ScholarTM
Check
Altmetric
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.