Award details

Flexible bayesian clustering and partition models for gene expression data

Reference	EGM16096
Principal Investigator / Supervisor	Professor Peter Green
Co-Investigators / Co-Supervisors
Institution	University of Bristol
Department	Mathematics
Funding type	Research
Value (£)	226,568
Status	Completed
Type	Research Grant
Start date	01/05/2002
End date	30/11/2006
Duration	55 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 28/EGM16093).

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:

EGM16093 Flexible bayesian clustering and partition models for gene expression data

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