Sponsored by: National Science Foundation (BES);

Project Number: 9814092

The objective of this project is to develop analytical tools that could be applied to genomic sequence information in order to predict the complete phenotype of an organism. This research is a combined effort between investigators at the University of California - San Diego (UCSD) and Harvard University (HU). The research will involve a dynamic interaction between algorithm development and mathematical representations of phenotypes (in silico analysis) and experimentally determined patterns of gene expression and growth. The in silico work will be performed at UCSD and the experimental work will be performed at HU. The three specific goals outlined are: (1) to develop algorithms that can use bioinformatic data bases to identify genes and their functions, predict the metabolic biochemistry a cell can perform, and represent the physiological behavior of a given strain based on its metabolism; (2) to develop algorithms that will predict the impact of altering the genotype on growth, metabolic flux and pathway utilization, and predict changes in genome-wide patterns of gene expression as a function of changes in growth conditions; and (3) to develop experimental approaches using E. coli K-12 to directly test the predictions made by in silico analysis. The approaches will involve the use of DNA chip technology to monitor genome-wide changes in gene expression in wild type cells under well-defined environmental conditions and the rigorous construction of isogenic strains whose metabolic activities can be experimentally determined and compared to the predictions generated by the in silico analysis.

Federal Contact Name:  
NSF Contact:   Fred G. Heineken   Phone:(703)306-1319

Last Revision: 02/18/2000