| EPSRC Reference: |
GR/K51662/01 |
| Title: |
NEURAL NETWORKS TO SUPPORT MOLECULAR STRUCTURE MATCHING |
| Principal Investigator: |
Austin, Professor J |
| Other Investigators: |
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| Researcher Co-Investigators: |
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| Project Partners: |
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| Department: |
Computer Science |
| Organisation: |
University of York |
| Scheme: |
Standard Research (Pre-FEC) |
| Starts: |
01 August 1995 |
Ends: |
31 July 1998 |
Value (£): |
138,672
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| EPSRC Research Topic Classifications: |
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| EPSRC Industrial Sector Classifications: |
| Creative Industries |
Pharmaceuticals and Biotechnology |
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Summary on Grant Application Form |
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This proposal aims to apply neural network methods to the problem of fast matching in molecular databases. Current systems that perform fast pre-screening of molecular structures rely on the use of pair wise atomic relations for the search. In contrast this work will investigate the use of neural networks to match the molecular electrostatic field potential and other molecular properties, which are seen to be more informative in chemical matching problems. The work will draw upon recent advances in neural network based associative memories that have been shown to yield very fast matching rates on uncertain data. The research will investigate the effect the neural architecture and the effect of varying the network parameters has on the performance of the networks. The work will investigate the possibility of deriving new molecular characteristics using neural network methods.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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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.york.ac.uk |