Award details

Flexible bayesian clustering and partition models for gene expression data

Reference	EGM16093
Principal Investigator / Supervisor	Professor Sylvia Richardson
Co-Investigators / Co-Supervisors	Professor Peter Green, Dr Emma Marshall
Institution	Imperial College London
Department	Imperial College London Department
Funding type	Research
Value (£)	460,184
Status	Completed
Type	Research Grant
Start date	01/03/2002
End date	28/02/2007
Duration	60 months

Abstract

The project aims to develop novel statistical tools to find biologically meaningful groupings in gene expression profiles across multiple samples. It will use Bayesian hierarchical models to integrate sources of variability, prior knowledge, assessment of uncertainty and the flexibility to cope with variable dimension problems. To ensure efficient knowledge transfer to the Microarray community, the tools developed will be installed in the Microarray Centre at Imperial College. The project is built around a close collaboration between statisticians and molecular biologists. Through these interactions, the essential interplay between relevant scientific questions arising from genomics experiments and model development will be accomplished. (Joint with grant 7/EGM16096).

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	Exploiting Genomics: Manufacturing & New Post Tech (EGM) [2001]
Funding Scheme	X – not Funded via a specific Funding Scheme

Associated awards:

EGM16096 Flexible bayesian clustering and partition models for gene expression data

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