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Studying biochemical networks using probabilistic knowledge discovery

Reference	BEP17011
Principal Investigator / Supervisor	Professor Stephen Muggleton
Co-Investigators / Co-Supervisors	Professor Michael Sternberg
Institution	Imperial College London
Department	Computing
Funding type	Research
Value (£)	434,060
Status	Completed
Type	Research Grant
Start date	01/05/2002
End date	31/08/2005
Duration	40 months

Abstract

The aim is to develop a formal and robust approach web-based tool to help biologists gather and interpret information about biochemical networks. Use of these tools by the community will provide new insights into systems biology. The formal approach will be implemented by using stochastic logic programs (SLPs). SLPs are well suited to deal with logical relationships stemming from the graphical nature of networks and with the uncertainty inherent to noisy and incomplete bioinformatic data sets from numerous sources. SLPs are a generalisation of Hidden Markov Models, stochastic-free grammars, and undirected Bayes nets. GRID technology will be used for updating the databases and to provide a web-based interface capable of uploading data from the users remote site.

Summary

unavailable

Committee	Closed Committee - Engineering & Biological Systems (EBS)
Research Topics	X – not assigned to a current Research Topic
Research Priority	X – Research Priority information not available
Research Initiative	Bioinformatics and E Science Programme (BEP) [2000-2001]
Funding Scheme	X – not Funded via a specific Funding Scheme

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