| EPSRC Reference: |
GR/S62383/01 |
| Title: |
Network Simulations in Bioinformatics |
| Principal Investigator: |
Higham, Professor D |
| Other Investigators: |
|
| Researcher Co-Investigators: |
|
| Project Partners: |
|
| Department: |
Mathematics and Statistics |
| Organisation: |
University of Strathclyde |
| Scheme: |
Standard Research (Pre-FEC) |
| Starts: |
30 April 2004 |
Ends: |
29 April 2007 |
Value (£): |
146,086
|
| EPSRC Research Topic Classifications: |
| Bioinformatics |
Logic & Combinatorics |
| Numerical Analysis |
|
|
| EPSRC Industrial Sector Classifications: |
| Pharmaceuticals and Biotechnology |
|
|
| Related Grants: |
|
| Panel History: |
| Panel Date | Panel Name | Outcome |
|
12 Sep 2003
|
Mathematics Prioritisation Panel (Science)
|
Deferred
|
|
|
Summary on Grant Application Form |
|
The sequencing of the human and other genomes, and the subsequent 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 their 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 throughput devices, such as microarrays, can generate large quantities of data, and because the data is inherently noisy, the modelling issue is challenging. We propose to use the recently developed class of range dependent random graphs as the basis for our modelling, as these graphs have the appropriate bias towards short-range links whilst still possessing the scale-free property that has been observed in practice. Developing an appropriate model will allow us to address high level questions concerning hierarchical properties, robustness to deletions, scaling of key properties 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. This 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 area.
|
|
Key Findings |
|
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
|
|
Potential use in non-academic contexts |
|
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
|
|
Impacts |
|
| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
|
| Date Materialised |
|
|
|
|
Sectors submitted by the Researcher |
|
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
|
| Project URL: |
|
| Further Information: |
|
| Organisation Website: |
http://www.strath.ac.uk |