Regularizing capacity of metabolic networks.
Despite their topological complexity almost all functional properties of metabolic networks can be derived from steady-state dynamics. Indeed, many theoretical investigations (like flux-balance analysis) rely on extracting function from steady states. This leads to the interesting question as to how metabolic networks avoid complex dynamics and maintain a steady-state behavior. Here, we expose metabolic network topologies to binary dynamics generated by simple local rules. We find that the networks' response is highly specific: Complex dynamics are systematically reduced on metabolic networks compared to randomized networks with identical degree sequences. Already small topological modifications substantially enhance the capacity of a network to host complex dynamic behavior and thus reduce its regularizing potential. This exceptionally pronounced regularization of dynamics encoded in the topology may explain why steady-state behavior is ubiquitous in metabolism.
Marr
Carsten
C
Bioinformatics Group, Department of Biology, Darmstadt University of Technology, D-64287 Darmstadt, Germany. marr@bio.tu-darmstadt.de
Müller-Linow
Mark
M
Hütt
Marc-Thorsten
MT
D000465:Algorithms; D001703:Biophysics / Q000379:methods*; D020134:Catalytic Domain; D002468:Cell Physiological Phenomena; D003198:Computer Simulation; D019277:Entropy; D053858:Metabolic Networks and Pathways; D008660:Metabolism; D008954:Models, Biological; D008959:Models, Neurological; D015233:Models, Statistical; D009991:Oscillometry; D049490:Systems Biology; D013816:Thermodynamics