Award details

Novel algorithms for gene expression time series

Reference	BB/C506264/1
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	Computer Science
Funding type	Research
Value (£)	178,256
Status	Completed
Type	Research Grant
Start date	14/02/2005
End date	13/02/2008
Duration	36 months

Abstract

The proposed research will examine at alternative computational framework called Simultaneous Modelling and Clustering (SMC) that will support the automation of the gene expression MTS analysis process. The SMC would cluster gene expression variables by scoring a candidate cluster on the predictive ability of a model that is built from variables within the cluster. A balanced optimisation strategy will be developed to allow quality models to be generated while managing to converge quickly. Novel scalable algorithms will be proposed to manage MTS involving thousands of variables as demonstrated in the microarray applications. A systematic evaluation of the SMC methods will be performed on a variety of virus and host interaction gene expression MTS using bioinformatics such as VIDA and BIOMAP. To speed up the process, approximate modelling methods will be developed and parallel algorithms designed for running on a computer farm. A collection of web-based tools for modelling short, high-dimensional gene expression MTS will be made available to scientists and biomedical researchers.

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	X - not in an Initiative
Funding Scheme	X – not Funded via a specific Funding Scheme

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