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A novel phylogenetic-statistical method for the discovery of protein-protein interactions in bioinformatics data

Reference	G19848
Principal Investigator / Supervisor	Professor Mark Pagel
Co-Investigators / Co-Supervisors	Dr Daniel Barker
Institution	University of Reading
Department	Animal and Microbial Sciences
Funding type	Research
Value (£)	208,547
Status	Completed
Type	Research Grant
Start date	01/08/2003
End date	31/07/2006
Duration	36 months

Abstract

We shall develop novel phylogenetically-based statistical methods for detecting protein-protein interactions across species. The methods will implement maximum likelihood statistical models for detecting correlated evolution in pairs of proteins, and use Bayesian Markov-Chain Monte Carlo (MCMC) methods to account for uncertainty in phylogenetic trees and in estimates of correlations. We will apply the methods to the approximately 10,000 annotated protein interactions in the MIPS Comprehensive Yeast Genome Database, and produce a publicly available database of predicted pairwise protein-protein interactions, as derived from our new approach. We will make our methods freely available on the web as easy-to-use bioinformatics software.

Summary

unavailable

Committee	Closed Committee - Genes & Developmental Biology (GDB)
Research Topics	X – not assigned to a current Research Topic
Research Priority	X – Research Priority information not available
Research Initiative	X - not in an Initiative
Funding Scheme	X – not Funded via a specific Funding Scheme

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