Random network based dynamic analysis for biochemical reaction system

Complex networks are studied across many fields of science, providing a unifying language to describe disparate systems ranging from social interactions to power grids. It has recently been used in gene regulation network, but so far the resulting networks have only been analyzed statically. In this paper, the biochemical reaction network (BRN) model is proposed based on the random graph theory and the dynamics of the network is analyzed on the molecular-scale. Given the initial state and the evolution rules of the biochemical network, we demonstrated how the biochemical reaction network achieving homeostasis via simulation. We also studied the dynamics of the biochemical reaction network in perspective of average degree and edges. The network features of biochemical reaction system were analyzed in both its initial state and equilibrium state. Further more, we compared the network features of the biochemical reaction network with those of the original random graph. © 2012 American Scientific Publishers. All rights reserved.