Details of Grant 

EPSRC Reference:	EP/K032402/1
Title:	Network Comparison
Principal Investigator:	Reinert, Professor G
Other Investigators:	Deane, Professor C
Researcher Co-Investigators:
Project Partners:
Department:	Statistics
Organisation:	University of Oxford
Scheme:	Standard Research
Starts:	01 October 2013	Ends:	31 December 2016	Value (£):	506,211
EPSRC Research Topic Classifications:	Statistics & Appl. Probability
EPSRC Industrial Sector Classifications:	Pharmaceuticals and Biotechnology
Related Grants:
Panel History:	Panel Date Panel Name Outcome 13 Mar 2013 Mathematics Prioritisation Panel Meeting March 2013 Announced
Summary on Grant Application Form
Networks are ubiquitous, a prime example being social network sites such as Facebook, and yet there is a lot which is not understood about them. Even for the seemingly simple question of how similar two networks are, to date there is no generally accepted method available to answer this question. The proposed project will address exactly this issue, how to compare networks. Network comparison is of considerable importance for example when trying to compare protein-protein interaction networks of organisms under different form of stress, or when trying to compare protein-protein interaction networks of people carrying a certain disease to that of people without the disease. The statistics will be applicable to any types of networks, and they could be used to track changes in networks over time. While constructing such a statistic for network comparison may be relatively straightforward, for statistical tests its probabilistic properties have to be understood. Achieving such understanding requires considerable expertise in probability, as there are a number of questions which have to be tackled in order to establish a useful asymptotic result. Similarly, the statistical properties of the new statistics have to be understood. How well do they separate models which are generated from just slightly different models? How can suitable test procedures be implemented? Preliminary studies have shown that our method can be used to reconstruct phylogenetic trees based on protein-protein interaction networks. If confirmed, then this is the first result which shows that the topology of protein-protein interaction networks alone contains information about evolution. This result is of considerable interest in biology, and its biological implications have to be studied in detail. Experience has seen that networks are able to capture the imagination, and are a suitable topic for outreach activities. Hence we intend to develop some lectures aimed at a general audience, to be offered to schools, via departmental contacts in the first instance, as well as at public science forums. There will be a blog about our research on the Oxford Sparks portal, an on-line public science website.
Key Findings
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Potential use in non-academic contexts
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Impacts
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Organisation Website:	http://www.ox.ac.uk