Evolution modeling algorithm of biochemical networks

Biological systems are extremely complex, nonlinear and self-organized, self-regulated systems that can adjust to the environmental changes due to underlying genetic mechanisms. The key task of systems biology is to understand cellular processes, functions and/or properties of biological system better. It can be done by means of the structure, behaviour and dynamic exploration of biochemical networks, such as genetic regulatory, metabolic, protein interaction and signalling networks. In this paper we focused on the modeling of biochemical networks evolution that occur as a result of genetic alterations and offer coterie an evolution modeling algorithm of biochemical network structure.