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a catalog of biological databases

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Database information

EKPD (Database of Eukaryotic Protein Kinases)

General information

Description: EKPD is a hierarchical database of eukaryotic protein kinases (PKs) and protein phosphatases (PPs),the key molecules responsible for the reversible phosphorylation of proteins that are involved in almost all aspects of biological processes
Year founded: 2014
Last update: 9/10/2013
Version: v1.1
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Country/Region: China
Data type:
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Contact information

University/Institution: Huazhong University of Science and Technology
Address: epartment of Biomedical Engineering,College of Life Science and Technology,Huazhong University of Science and Technology,Wuhan,Hubei 430074,China
City: Wuhan
Province/State: Hubei
Country/Region: China
Contact name (PI/Team): Yu Xue
Contact email (PI/Helpdesk): xueyu@hust.edu.cn

Record metadata

Created on: 2015-06-20
Curated by:
Jian SA [2016-04-04]
Jian SA [2015-12-08]
Jian SA [2015-07-01]
Jian SA [2015-06-27]

Ranking

All databases:
1623/4525 (64.155%)
Interaction:
250/669 (62.78%)
1623
Total Rank
21
Citations
3.5
z-index

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Publications

24214991
EKPD: a hierarchical database of eukaryotic protein kinases and protein phosphatases. [PMID: 24214991]
Wang Y, Liu Z, Cheng H, Gao T, Pan Z, Yang Q, Guo A, Xue Y.

We present here EKPD (http://ekpd.biocuckoo.org), a hierarchical database of eukaryotic protein kinases (PKs) and protein phosphatases (PPs), the key molecules responsible for the reversible phosphorylation of proteins that are involved in almost all aspects of biological processes. As extensive experimental and computational efforts have been carried out to identify PKs and PPs, an integrative resource with detailed classification and annotation information would be of great value for both experimentalists and computational biologists. In this work, we first collected 1855 PKs and 347 PPs from the scientific literature and various public databases. Based on previously established rationales, we classified all of the known PKs and PPs into a hierarchical structure with three levels, i.e. group, family and individual PK/PP. There are 10 groups with 149 families for the PKs and 10 groups with 33 families for the PPs. We constructed 139 and 27 Hidden Markov Model profiles for PK and PP families, respectively. Then we systematically characterized ?50,000 PKs and >10,000 PPs in eukaryotes. In addition, >500 PKs and >400 PPs were computationally identified by ortholog search. Finally, the online service of the EKPD database was implemented in PHP + MySQL + JavaScript.

Nucleic Acids Res. 2014:42(Database issue) | 21 Citations (from Europe PMC, 2020-01-25)