Neocybernetic Modeling of a Biological Cell

A biological cell forms an extremely complex system with a complicated metabolic reaction network. The functionality of the cell is controlled by the genome consisting of thousands of individual genes. Novel measurement technologies provide us with huge amounts of biological data in a quantitative form, but the suitable modeling methods to deal with the high dimensionality and large systems are still missing. In this article, a novel approach for complex system analysis, neocybernetics, is applied to modeling a biological cell. It is shown that under certain assumptions both the metabolic network and the gene expression network can be interpreted as a combined linear system. The analysis of this system from the neocybernetic starting points is then elaborated. As an example, the dynamics of yeast gene expression network are modeled according to the presented principles.