Database Commons
Database Commons

a catalog of worldwide biological databases

Database Profile

EDK

General information

URL: https://bigd.big.ac.cn/edk
Full name: Editome Disease Knowledgebase
Description: an integrated knowledgebase of RNA editome-disease associations manually curated from published literatures.
Year founded: 2019
Last update: 2018-10-10
Version: v1.0
Accessibility:
Manual:
Accessible
Real time : Checking...
Country/Region: China

Classification & Tag

Data type:
RNA
Data object:
Database category:
Major species:
Keywords:

Contact information

University/Institution: Beijing Institute of Genomics, Chinese Academy of Sciences
Address: No.1 Beichen West Road, Chaoyang District, Beijing 100101, China
City: Beijing
Province/State: Beijing
Country/Region: China
Contact name (PI/Team): Zhang Zhang
Contact email (PI/Helpdesk): zhangzhang@big.ac.cn

Publications

30357418
Editome Disease Knowledgebase (EDK): a curated knowledgebase of editome-disease associations in human. [PMID: 30357418]
Niu G, Zou D, Li M, Zhang Y, Sang J, Xia L, Li M, Liu L, Cao J, Zhang Y, Wang P, Hu S, Hao L, Zhang Z.

RNA editing, as an essential co-/post-transcriptional RNA modification type, plays critical roles in many biological processes and involves with a variety of human diseases. Although several databases have been developed to collect RNA editing data in both model and non-model animals, there still lacks a resource integrating associations between editome and human disease. In this study, we present Editome-Disease Knowledgebase (EDK; http://bigd.big.ac.cn/edk), an integrated knowledgebase of RNA editome-disease associations manually curated from published literatures. In the current version, EDK incorporates 61 diseases associated with 248 experimentally validated abnormal editing events located in 32 mRNAs, 16 miRNAs, 1 lncRNA and 11 viruses, and 44 aberrant activities involved with 6 editing enzymes, which together are curated from more than 200 publications. In addition, to facilitate standardization of editome-disease knowledge integration, we propose a data curation model in EDK, factoring an abundance of relevant information to fully capture the context of editome-disease associations. Taken together, EDK is a comprehensive collection of editome-disease associations and bears the great utility in aid of better understanding the RNA editing machinery and complex molecular mechanisms associated with human diseases.

Nucleic Acids Res. 2019:47(D1) | 18 Citations (from Europe PMC, 2024-04-06)

Ranking

All databases:
2179/6000 (63.7%)
Modification:
129/287 (55.401%)
Health and medicine:
500/1394 (64.204%)
Literature:
200/531 (62.524%)
2179
Total Rank
18
Citations
3.6
z-index

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Record metadata

Created on: 2019-01-03
Curated by:
Dong Zou [2020-12-11]
Dong Zou [2019-01-08]
Dong Zou [2019-01-03]