Database Commons

a catalog of biological databases

e.g., animal; RNA; Methylation; China

Database Profile

General information

Full name: MeDReaders: A database for transcription factors that bind to methylated DNA
Description: The current version of the database allows users to A) achieve methylated DNA binding motifs of TFs of user's interest or search potential TFs by matching methylated binding sequences as user requested. B) obtain and/or compare methylation contexts of the same TF under different cell lines and/or tissues. C) download position weight matrix (PWM) of TFs associated with methylation status (high or low methylation). D)submit newly published information of methylated-DNA binding TFs to enrich our database.
Year founded: 2017
Last update:
Version: v1.0
Real time : Checking...
Country/Region: United States
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Contact information

University/Institution: Johns Hopkins University
Address: Room 333, Edward D. Miller Research Building, 733 N. Broadway, Baltimore, MD 21205
City: baltimore
Country/Region: United States
Contact name (PI/Team): Heng Zhu
Contact email (PI/Helpdesk):


MeDReaders: a database for transcription factors that bind to methylated DNA. [PMID: 29145608]
Wang G, Luo X, Wang J, Wan J, Xia S, Zhu H, Qian J, Wang Y.

Understanding the molecular principles governing interactions between transcription factors (TFs) and DNA targets is one of the main subjects for transcriptional regulation. Recently, emerging evidence demonstrated that some TFs could bind to DNA motifs containing highly methylated CpGs both in vitro and in vivo. Identification of such TFs and elucidation of their physiological roles now become an important stepping-stone toward understanding the mechanisms underlying the methylation-mediated biological processes, which have crucial implications for human disease and disease development. Hence, we constructed a database, named as MeDReaders, to collect information about methylated DNA binding activities. A total of 731 TFs, which could bind to methylated DNA sequences, were manually curated in human and mouse studies reported in the literature. In silico approaches were applied to predict methylated and unmethylated motifs of 292 TFs by integrating whole genome bisulfite sequencing (WGBS) and ChIP-Seq datasets in six human cell lines and one mouse cell line extracted from ENCODE and GEO database. MeDReaders database will provide a comprehensive resource for further studies and aid related experiment designs. The database implemented unified access for users to most TFs involved in such methylation-associated binding actives. The website is available at

Nucleic Acids Res. 2018:46(D1) | 25 Citations (from Europe PMC, 2021-06-19)


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178/771 (77.043%)
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Record metadata

Created on: 2018-01-28
Curated by:
Nashaiman Pervaiz [2018-12-28]
huma shireen [2018-04-03]