Reed, Jennifer L.

Reed JL, Patel TR, Chen KH, Joyce AR, Applebee MK, Herring CD, Bui OT, Knight EM, Fong SS, and Palsson BO. Systems Approach to Refining Genome Annotation: Prediction and Validation of Gene Functions. Proc Natl Acad Sci U S A. 103(46):17480-17484 (2006).
Joyce AR, Reed JL, White A, Edwards R, Osterman A, Baba T, Mori H, Lesley SA, Palsson BO, and Agarwalla S*. Experimental and computational assessment of conditionally essential genes in E. coli. J Bacteriology. 188(23): 8259-8271 (2006).
Covert MW, Knight EM, Reed JL, Herrgard MJ, and Palsson BO. Integrating high-throughput data and computational models leads to E. coli network elucidation. Nature. 429: 92-96 (2004).
Reed JL, Vo TD, Schilling CH, and Palsson BO. An expanded genome-scale model of Escherichia coli K-12 (iJR904 GSM/GPR). Genome Biology. 4(9): p. R54.1-R54.12 (2003).
Reed JL, Famili I, Thiele I, and Palsson BO. Towards Multidimensional Genome Annotation. Nature Reviews Genetics. 7(2):130-141 (2006).
Price ND, Reed JL, and Palsson BO. Genome-scale Models of Microbial Cells: Evaluating the consequences of constraints. Nature Reviews Microbiology. 2:886-897 (2004).

Selected Awards, Honors and Societies

University of California Faculty Fellow (2005-2007)
Irwin and Joan Jacobs Fellow (2000-2001)

Summary

Systems biology utilizes both experimental and computational approaches to study biological networks at a systems or whole network level, in order to understand and predict cellular behavior. Computational efforts need to be able to account qualitatively and quantitatively for a wide range of different data types relevant to biological systems. Most of my research group's interests involve the study of metabolism and regulation through the generation and subsequent analysis of metabolic models and reconciliation with experimental data. Overall, my group uses computational models and develops methods to study biological systems, engineer cells, and expand our knowledge of the underlying mechanisms behind observed cellular behavior.

My group is interested in building, analyzing, and utilizing metabolic and regulatory models of organisms involved in bioremediation, biofuels, and pharmaceutical applications. Once developed these models can be used to evaluate the capabilities of different organisms from a network-based perspective and to identify ways in which genetic manipulations could enhance their productivity. Additional experimental efforts in the group allow us to gather experimental data needed for model building and testing.

In addition to model building, we are also interested in developing computational methods for designing strains or cell lines with enhanced production yields of desired products. These computational methods will account for both metabolic and regulatory effects occurring inside the cell. Models that determine intracellular flux distributions can also be used to identify potential metabolic or regulatory roadblocks that might be limiting production in developed strains.

We are also interested in using the developed models to identify novel gene functions or regulatory interactions, further clarifying the roles gene products play within the cell. By developing model analysis and bioinformatics methods, we can generate hypotheses regarding cellular metabolism and regulation. Subsequent experimental testing is conducted to confirm or reject these model-generated hypotheses.

Files and Links of Interest

Available PostDoc Positions

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Date last modified: 29-Apr-2008
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