Jennifer L. Reed

Associate Professor

3639 Engineering Hall
1415 Engineering Drive
Madison, WI 53706

Ph: (608) 262-0188
Fax: (608) 262-5434
reed@engr.wisc.edu

Primary Affiliation:
Chemical and Biological Engineering

Additional Affiliations:
Biomedical Engineering,


Profile Summary

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. 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. 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. 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.

Education

  • BS, University of California, San Diego
  • MS, University of California, San Diego
  • PhD, University of California, San Diego

Research Interests

  • Systems biology
  • Metabolic model development & analysis
  • Metabolic engineering
  • Biofuels, bioremediation, & biotechnology

Awards, Honors and Societies

  • Irwin and Joan Jacobs Fellow (2000-2001)
  • University of California Faculty Fellow (2005-2007)
  • NSF Career Awardee (2011)
  • DOE Early Career Awardee (2012)

Publications

  • 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).
  • Reed JL, Famili I, Thiele I, and Palsson BO. Towards Multidimensional Genome Annotation. Nature Reviews Genetics. 7(2):130-141 (2006).
  • 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).
  • 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).
  • 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).
  • 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).
  • Feist AM, Herrgard MJ, Thiele I, Reed JL and Palsson BO. Reconstruction of Biochemical Networks in Microbial Organisms. Nature Reviews Microbiology, 7(2):129-43 (2009)
  • Raghunathan A, Reed JL, Shin S, Palsson BO, and Daefler S. Constraint-Based Analysis of Metabolic Capacity of Salmonella Typhimurium During Host-Pathogen Interaction. BMC Systems Biology, 3:38 (2009)

Courses

Fall 2014-2015

  • CBE 890 - Pre-Dissertator\'s Research

  • CBE 790 - Master\'s Research or Thesis
  • CBE 699 - Advanced Independent Studies
  • CBE 599 - Special Problems
  • CBE 990 - Thesis-Research
  • Profile Summary

    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. 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. 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. 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.


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