EPSRC Reference: |
GR/S62390/01 |
Title: |
Network Simulations in Bioinformatics |
Principal Investigator: |
Spence, Professor A |
Other Investigators: |
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Researcher Co-Investigators: |
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Project Partners: |
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Department: |
Mathematical Sciences |
Organisation: |
University of Bath |
Scheme: |
Standard Research (Pre-FEC) |
Starts: |
01 August 2004 |
Ends: |
31 October 2007 |
Value (£): |
73,421
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EPSRC Research Topic Classifications: |
Bioinformatics |
Logic & Combinatorics |
Numerical Analysis |
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EPSRC Industrial Sector Classifications: |
Pharmaceuticals and Biotechnology |
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Related Grants: |
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Panel History: |
Panel Date | Panel Name | Outcome |
12 Sep 2003
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Mathematics Prioritisation Panel (Science)
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Deferred
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Summary on Grant Application Form |
The sequance of the human and other genomes, and the subsequant research effort to exploit this information, has led to the generation of data sets that are so large as to require new mathematical tools for their analysis. This proposal deals with many to many relationships between genes, or the proteins they code for, and ther functions. Early work in this area has used clustering concepts that are inherently many to one . We propose to represent this data as a graph. Because newly emerging high troughput devices, such as microarrays, can generatelarge quantities of data, and because the data is inherently noisy, the modelling issue is challenging. We proposae to use the recently devloped cass of range dependent random graphs as the basis for our modelling, as the graphs have the appropriate bias towards short-range links whilst still processing the scale-free property that has been observed in practise. Devloping an approprite model will allow us to address high level questions concerning hierarchical propoerties, robustness to deletions, scaling of key propoerties with respect to network size and evolution of connections over time. A second thrust is to develop computational algorithms for extracting structural information from network data. The process is extremely important if technological advances in data collection are to produce practical dividends in biochemistry and medicine. We believe that this proposal has added value due to its synthesis of novel research in modelling and computational mathematics and a high-profile, rapidly expanding, application are.
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Key Findings |
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Potential use in non-academic contexts |
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Impacts |
Description |
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Summary |
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Date Materialised |
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Sectors submitted by the Researcher |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Project URL: |
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Further Information: |
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Organisation Website: |
http://www.bath.ac.uk |