Descriptive and predictive applications of constraint-based metabolic models.
Constraint-based models of metabolism are becoming available for an increasing number of organisms. These models can be used in combination with existing experimental data to describe the behavior of an organism and to analyze experimental observations in the context of a model. Such a descriptive application of the models can also allow for the integration of various types of data. Additionally, these models can be used in a predictive fashion to hypothesize the outcomes of new experiments. Comparing model predictions with experimental results allows for the iterative improvement of developed models and increases our understanding of the organism being studied. A number of recent examples of both descriptive and predictive applications of constraint-based models are discussed.
Reed
Jennifer L
JL
University of Wisconsin-Madison, Madison, WI 53706 USA. reed@engr.wisc.edu
D000465:Algorithms; D003198:Computer Simulation; D004926:Escherichia coli / Q000378:metabolism*; D029968:Escherichia coli Proteins / Q000378:metabolism*; D008954:Models, Biological; D015398:Signal Transduction / Q000502:physiology*
D029968:Escherichia coli Proteins