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Bioinformatics Advance Access originally published online on January 28, 2009
Bioinformatics 2009 25(5):684-686; doi:10.1093/bioinformatics/btp026
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© 2009 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

KEA: kinase enrichment analysis

Alexander Lachmann and Avi Ma'ayan *

Department of Pharmacology and Systems Therapeutics, Systems Biology Center in New York, Icahn Medical Institute, Mount Sinai School of Medicine, 1425 Madison Avenue, New York, NY 10029, USA

*To whom correspondence should be addressed.


  Abstract

Motivation: Multivariate experiments applied to mammalian cells often produce lists of proteins/genes altered under treatment versus control conditions. Such lists can be projected onto prior knowledge of kinase–substrate interactions to infer the list of kinases associated with a specific protein list. By computing how the proportion of kinases, associated with a specific list of proteins/genes, deviates from an expected distribution, we can rank kinases and kinase families based on the likelihood that these kinases are functionally associated with regulating the cell under specific experimental conditions. Such analysis can assist in producing hypotheses that can explain how the kinome is involved in the maintenance of different cellular states and can be manipulated to modulate cells towards a desired phenotype.

Summary: Kinase enrichment analysis (KEA) is a web-based tool with an underlying database providing users with the ability to link lists of mammalian proteins/genes with the kinases that phosphorylate them. The system draws from several available kinase–substrate databases to compute kinase enrichment probability based on the distribution of kinase–substrate proportions in the background kinase–substrate database compared with kinases found to be associated with an input list of genes/proteins.

Availability: The KEA system is freely available at http://amp.pharm.mssm.edu/lib/kea.jsp

Contact: avi.maayan{at}mssm.edu

Associate Editor: Burkhard Rost

Received on November 8, 2008; revised on December 19, 2008; accepted on January 8, 2009

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