Award details

Analysing virus gene expression data to understand regulatory interactions

Reference	BIO14300
Principal Investigator / Supervisor	Professor Xiaohui Liu
Co-Investigators / Co-Supervisors	Professor Paul Kellam, Dr Nigel John Martin, Professor Christine Orengo
Institution	Brunel University London
Department	Information Systems & Computing
Funding type	Research
Value (£)	140,176
Status	Completed
Type	Research Grant
Start date	01/04/2001
End date	01/01/2005
Duration	45 months

Abstract

This proposal seeks to understand how to determine the genetic network of molecular interactions using gene expression data. After extending an existing virus database, ViDA, to include the expression array component, we will initially examine the data by applying clustering algorithms and related data pre- processing techniques. We will then construct models for understanding the underlying regulatory interactions from the expression data. Two multivariate time series methods will be used: the Vector Auto- Regressive Process and the Dynamic Bayesian Networks. Finally, relevant protein structures, functions, and transcriptional control mechanisms will be used to validate the models.

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 (Phase 2) (BIO) [1998-2000]
Funding Scheme	X – not Funded via a specific Funding Scheme

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