Robustness as a measure of plausibility in models of biochemical networks.
Theory, experiment, and observation suggest that biochemical networks which are conserved across species are robust to variations in concentrations and kinetic parameters. Here, we exploit this expectation to propose an approach to model building and selection. We represent a model as a mapping from parameter space to behavior space, and utilize bifurcation analysis to study the robustness of each region of steady-state behavior to parameter variations. The hypothesis that potential errors in models will result in parameter sensitivities is tested by analysis of two models of the biochemical oscillator underlying the Xenopus cell cycle. Our analysis successfully identifies known weaknesses in the older model and suggests areas for further investigation in the more recent, more plausible model. It also correctly highlights why the more recent model is more plausible.
Morohashi
Mineo
M
Systems Biology Group Tokyo & Caltech Unit, ERATO Kitano Symbiotic Systems Project, Japan Science and Technology Corporation, M-31 Suite 6A, 6-31-15, Jingumae Shibuya-ku, Tokyo 150-0001, Japan.
Winn
Amanda E
AE
Borisuk
Mark T
MT
Bolouri
Hamid
H
Doyle
John
J
Kitano
Hiroaki
H
D000818:Animals; D001669:Biochemical Phenomena; D002453:Cell Cycle; D008954:Models, Biological; D014981:Xenopus