UNDERSTANDING BIOLOGICAL SYSTEMS:
Predicting cell behavior from fundamentals by Jennie Reed
 ystems biology utilizes both experimental and computational approaches to study biological networks at a systems (i.e. whole network) level. By studying how cellular components interact at a systems level, we can get a better understanding of how cells control their behavior, allowing us to make predictions about how cells would respond to perturbations.
Experimental techniques are available that allow us to measure the abundance of cellular components and detect component interactions. Computational approaches can be used to analyze and integrate various types of high-throughput data (including genomic, proteomic, and transcriptomic data), as well as to construct predictive models of cellular behavior.
Our group is interested in combining modeling and experimental efforts in order to study biological systems with industrial, pharmaceutical, and/or bioremediation applications.
Our research involves:
• 1) the construction and analysis of metabolic and regulatory models for various organisms,
• 2) the development of computational methods for cellular engineering, and
• 3) the development of methods for model-guided discovery of new components and component interactions in biological networks. The modeling work thus generates hypotheses that we can then test experimentally.
Computational models play a central role in our research, where the generation and subsequent analysis of models leads to hypotheses that we can test in the lab. In addition to building models, we are also interested in developing computational methods to identify modifications needed for engineering cells with enhanced production yields for desired products, such as ethanol. For example, we can determine computationally what enzyme encoding genes we should introduce or remove from the organism in order to improve ethanol production. We are also interested in using the developed models to identify novel gene functions or new regulatory interactions, further clarifying the roles gene products play within the cell.
By developing new computational methods we will increase the utility of models for biological research as well as improve the capabilities of organisms for different applications.
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