Schedule Mar 07, 2008
Simplifying Biological Models without Loss of Information
Natalie Arkus (Harvard)

Authors: Natalie Arkus, Michael Brenner
Harvard University

There is an abundance of models in biology that contain many equations and unknown parameters. Given the parameter and equation uncertainty inherent in these models, it is difficult to make definitive conclusions about a system or to obtain testable predictions. Simple models have the advantage of accomplishing both of these things; however, they often ignore much known biological information. Here, we present a method of simplifying complex biological systems such that they retain all biological information. The resulting reduced systems can be both directly testable, understandable, and showcase which components are most significant biologically. As examples, we consider models of the E. coli heat shock response system and of the Wnt signaling pathway.
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