Evolution - Based Gene Regulatory Network of Yeast Cell Cycle

In the work, we try to construct the corresponding S-system and modified power-low model from a dataset. These two mathematical models are highly nonlinear. Though they can clearly describe reactions among genes in the biological system, the identification is a tough work, especially for huge genes. We adopt the evolution strategy to achieve 16-genes modeling with 544 or 288 parameters. The time-course data of the yeast cell cycle is concerned. The proposed two different gene regulatory networks and their corresponding pathways can provide biological researchers for further experiments in yeast cell cycle control.