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Analysis and enhanced representation of protein interaction networks: towards understanding the evolution of complex intracellular systems

Reference	BB/C515412/1
Principal Investigator / Supervisor	Professor David Robertson
Co-Investigators / Co-Supervisors	Mr Gregory Amoutzias
Institution	The University of Manchester
Department	Life Sciences
Funding type	Research
Value (£)	183,707
Status	Completed
Type	Research Grant
Start date	03/10/2005
End date	02/10/2008
Duration	36 months

Abstract

In recent years there has been a huge increase in research into biological networks such that there are now extensive large-scale eukaryote protein interaction data sets available. Despite the current limitations of the types of experimental studies from which these data sets are derived, the mapping of biological networks (the field of interactomics) will not only remain a major focus for many researchers, but it will improve in both accuracy and reliability leading ultimately to a true representation of all of the protein interactions in a cell. Current depictions of protein interaction networks are usually a graph with the nodes representing proteins and interactions (physical or functional) indicated as directed or undirected links. However the visualisation of the majority of protein interaction networks is not (usually) all that helpful to the researcher, beyond indicating that significant complexity is present or that specific functionally related clusters exist. In this project we aim to 1) investigate the molecular evolution of the interactome, focusing on protein-protein and protein-DNA interactions for which data is available or can be obtained by text-mining the preliminary literature, and 2) to develop new analytical tools that more formally integrate biological knowledge into network representation so as to enable more meaningful visualisations of the interactome. We will tackle the first aim by using omic databases and resources to provide a better understanding of the evolution of interaction networks by comparing networks from divergent species, by investigating the nature of change in complex networks and the significance of cross-talk between sub-networks/functional modules. The second aim will be tackled by using biological knowledge (e.g. homology/evolutionary relationships, gene/chromosomal location, cellular location, gene regulation/expression, function etc) to (i) cluster and spatially distribute interactive processes to introduce order in the protein-protein and protein-DNA networks, (ii) compare networks (particularly from different species) through the projection of abstract properties of graphs onto topological surfaces, and (iii) integrate regulatory proteins, their target-genes and protein-protein interaction networks. Accomplishing some of these objectives will make use of diagnostic tools from graph theory, for example, line graphs and hypergraphs.

Summary

unavailable

Committee	Closed Committee - Engineering & Biological Systems (EBS)
Research Topics	Technology and Methods Development
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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