Phosphoregulators: Protein kinases and protein phosphatases of mouse

Forrest, Alistair R. R., Ravasi, Timothy, Taylor, Darrin, Huber, Thomas L., Hume, David A., RIKEN GER Group, GSL Members and Grimmond, Sean (2003) Phosphoregulators: Protein kinases and protein phosphatases of mouse. Genome Research, 13 6B: 1443-1454. doi:10.1101/gr.954803

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Author Forrest, Alistair R. R.
Ravasi, Timothy
Taylor, Darrin
Huber, Thomas L.
Hume, David A.
GSL Members
Grimmond, Sean
Title Phosphoregulators: Protein kinases and protein phosphatases of mouse
Journal name Genome Research   Check publisher's open access policy
ISSN 1088-9051
Publication date 2003-06-01
Sub-type Article (original research)
DOI 10.1101/gr.954803
Open Access Status File (Publisher version)
Volume 13
Issue 6B
Start page 1443
End page 1454
Total pages 12
Editor L. Goodman
Place of publication Cold Spring Harbor, NY, United States
Publisher Cold Spring Harbor Laboratory Press
Language eng
Abstract With the completion of the human and mouse genome sequences, the task now turns to identifying their encoded transcripts and assigning gene function. In this study, we have undertaken a computational approach to identify and classify all of the protein kinases and phosphatases present in the mouse gene complement. A nonredundant set of these sequences was produced by mining Ensembl gene predictions and publicly available cDNA sequences with a panel of InterPro domains. This approach identified 561 candidate protein kinases and 162 candidate protein phosphatases. This cohort was then analyzed using TribeMCL protein sequence similarity clustering followed by CLUSTALV alignment and hierarchical tree generation. This approach allowed us to (1) distinguish between true members of the protein kinase and phosphatase families and enzymes of related biochemistry, (2) determine the structure of the families, and (3) suggest functions for previously uncharacterized members. The classifications obtained by this approach were in good agreement with previous schemes and allowed us to demonstrate domain associations with a number of clusters. Finally, we comment on the complementary nature of cDNA and genome-based gene detection and the impact of the FANTOM2 transcriptome project.
Keyword Biotechnology & Applied Microbiology
Genetics & Heredity
Functional Annotation
Q-Index Code C1
Institutional Status UQ

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Created: Wed, 15 Aug 2007, 12:47:43 EST