Dynamics on networks: Chemical reactions as a unifying framework

The study of complex networks has uncovered many unifying topological principles from a plethora of apparently unrelated applications. However, progress has been slower in understanding dynamical processes taking place on networks. This difficulty largely arises from the diversity of networks and their inherent nonlinearities. Here, we demonstrate that chemical reactions can serve as a unifying framework for studying deterministic and stochastic processes on networks from the fields of cell biology, epidemiology, ecology, sociology, and game theory. This allows advanced techniques for the modeling, reverse engineering, and analysis of chemical reaction networks to be applied to a wide variety of applications with relative ease.