Skip to main navigation Skip to search Skip to main content

M6ADD: a comprehensive database of m6A modifications in diseases

  • Dianshuang Zhou
  • , Hongli Wang
  • , Fanqi Bi
  • , Jie Xing
  • , Yue Gu
  • , Cong Wang
  • , Menyan Zhang
  • , Yan Huang
  • , Jiaqi Zeng
  • , Qiong Wu
  • , Yan Zhang*
  • *Corresponding author for this work
  • School of Life Science and Technology, Harbin Institute of Technology
  • Guangzhou Medical College

Research output: Contribution to journalArticlepeer-review

Abstract

N6-methyladenosine (m6A) modification is an important regulatory factor affecting diseases, including multiple cancers and it is a developing direction for targeted disease therapy. Here, we present the M6ADD (m6A-diseases database) database, a public data resource containing manually curated data on potential m6A-disease associations for which some experimental evidence is available; the related high-throughput sequencing data are also provided and analysed by using different computational methods. To give researchers a tool to query the m6A modification data, the M6ADD was designed as a web-based comprehensive resource focusing on the collection, storage and online analysis of m6A modifications, aimed at exploring the associations between m6A modification and gene disorders and diseases. The M6ADD includes 222 experimentally confirmed m6A-disease associations, involving 59 diseases from a review of more than 2000 published papers. The M6ADD also includes 409,229 m6A-disease associations obtained by computational and statistical methods from 30 high-throughput sequencing datasets. In addition, we provide data on 5239 potential m6A regulatory proteins related to 24 cancers based on network analysis prediction methods. In addition, we have developed a tool to explore the function of m6A-modified genes through the protein–protein interaction networks. The M6ADD can be accessed at http://m6add.edbc.org/.

Original languageEnglish
Pages (from-to)2354-2362
Number of pages9
JournalRNA Biology
Volume18
Issue number12
DOIs
StatePublished - 2021
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Ma modification
  • diseases
  • experimentally confirmed data
  • high-throughput sequencing data

Fingerprint

Dive into the research topics of 'M6ADD: a comprehensive database of m6A modifications in diseases'. Together they form a unique fingerprint.

Cite this