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.