Award details

Improved processing of microarray data with probabilistic models

Reference	BBS/B/0076X/2
Principal Investigator / Supervisor	Professor Neil Lawrence
Co-Investigators / Co-Supervisors
Institution	The University of Manchester
Department	Computer Science
Funding type	Research
Value (£)	54,088
Status	Completed
Type	Research Grant
Start date	01/07/2007
End date	30/06/2008
Duration	12 months

Abstract

Microarray analysis allows the simultaneous evaluation of thousands of gene expression levels. In recent years both cDNA microarrays and oligonucleotide based arrays have become established technologies for genomic analysis across biology. Once the biological processes are complete the raw date generated from both the oligonucleotide arrays and the cDNA arrays consists of an image. This proposal concerns itself with the processing of the arrays once the image has been generated. We will use probabilistic models to extract information from the data, beginning with the image analysis, followed by normalisation and finally data mining. We will use Bayesian methods to integrate and propagate errors inherent in each stage of the probabilistic modelling process, eventually providing the biologist with levels of confidence for inferences made from the data. (Joint with BBS/B/00778)

Summary

unavailable

Committee	Closed Committee - Engineering & Biological Systems (EBS)
Research Topics	Technology and Methods Development
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

Associated awards:

BBS/B/0076X Improved processing of microarray data with probabilistic models

BBS/B/00778 Improved processing of microarray data with probabilistic models

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