| URL: | https://ngdc.cncb.ac.cn/edk |
| Full name: | Editome Disease Knowledgebase |
| Description: | a repository of editome-disease associations aimed to decoding human diseases from transcriptome to editome. |
| Year founded: | 2019 |
| Last update: | 2024-12-10 |
| Version: | v2.0 |
| Accessibility: |
Accessible
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| Country/Region: | China |
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| 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 |
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Editome Disease Knowledgebase v2.0: an updated resource of editome-disease associations through literature curation and integrative analysis. [PMID: 39968378]
MOTIVATION: Editome Disease Knowledgebase (EDK) is a curated resource of knowledge between RNA editome and human diseases. Since its first release in 2018, a number of studies have discovered previously uncharacterized editome-disease associations and generated an abundance of RNA editing datasets. Thus, it is desirable to make significant updates for EDK by incorporating more editome-disease associations as well as their related editing profiles. |
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Editome Disease Knowledgebase (EDK): a curated knowledgebase of editome-disease associations in human. [PMID: 30357418]
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. |