Award details

Hierarchical plant metabolomics for gene function and mode of action (MOA)

Reference	EGA17719
Principal Investigator / Supervisor	Professor Ian Graham
Co-Investigators / Co-Supervisors
Institution	University of York
Department	Biology
Funding type	Research
Value (£)	217,480
Status	Completed
Type	Research Grant
Start date	01/04/2003
End date	31/03/2006
Duration	36 months

Abstract

Exploitation of genome sequences on public databases requires integrated approaches to determine gene function. Rapid phenotype fingerprinting is essential to exploit reverse genetics resources, such as the ATIS gene tag Arabidopsis mutant collection. We propose a hierarchical metabolomics approach opening with machine learning computational of high-throughput analysis of plant metabolites to facilitate comprehensive gene function determination. A major output will be a metabolome fingerprint database that will provide the basis of future applied post-genomic technologies for high-throughput mode- of-action analysis for agrochemical discovery as well as plant breeding, substantial equivalence testing of GMOs and food quality assessment. (Joint with grants 17716, 17717 and 17718).

Summary

unavailable

Committee	Closed Committee - Genes & Developmental Biology (GDB)
Research Topics	X – not assigned to a current Research Topic
Research Priority	X – Research Priority information not available
Research Initiative	Exploiting Genomics: Agri, Food and Environment (EGA) [2001]
Funding Scheme	X – not Funded via a specific Funding Scheme

Associated awards:

EGA17716 Hierarchical plant metabolomics for gene function and mode of action discovery

EGA17717 Hierarchical plant metabolomics for gene function and mode of action (MOA)

EGA17718 Heirachical plant metabolomics for gene function and mode of action

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