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A hybrid meta-heuristic approach to simplified sequence-structure-function problems

Reference	BIO14458
Principal Investigator / Supervisor	Professor Jonathan Hirst
Co-Investigators / Co-Supervisors	Professor Edmund Burke, Professor Peter Cowling, Professor Graham Kendall, Professor Sanja Petrovic
Institution	University of Nottingham
Department	Sch of Chemistry
Funding type	Research
Value (£)	134,844
Status	Completed
Type	Research Grant
Start date	20/08/2001
End date	03/02/2005
Duration	41 months

Abstract

We will develop novel optimisation techniques from Computer Science and IT and apply them to sequence- structure and sequence-function relationships. Recent successes in complex optimisation problems suggest that established methods (such as genetic algorithms, tabu search, simulated annealing) and emerging approaches (e.g. ant algorithms, case-based reasoning and variable neighbourhood search) warrant investigation in Bioinformatics. We will conduct extensive studies of simplified problems, so that the approaches can be developed, studied and appropriately hybridised, prior to application to real problems, where lack of data and noise can obscure algorithmic deficiencies. We propose then to apply the hybrid meta-heuristic approach to real problems, including protein sequence design and ab initio folding.

Summary

unavailable

Committee	Closed Committee - Biomolecular Sciences (BMS)
Research Topics	X – not assigned to a current Research Topic
Research Priority	X – Research Priority information not available
Research Initiative	Bioinformatics (Phase 2) (BIO) [1998-2000]
Funding Scheme	X – not Funded via a specific Funding Scheme

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