Evolving Model Of Protein-protein Interaction Networks

With the arrival of the post-genomic era, scientists have already overcome the difficulties in getting the structural information of genes; the function of gene has become a hot research point in systems biology. As we know, the product of gene is the corresponding proteins, which indicates that the sciencefic research on the biological function of proteins is the first step in understanding the function of the genes. The function of proteins is often reflected in the interaction with other proteins. Furthermore, proteins are involved in the realizations of various celluar physiological processes, such as signal transduction, reaction to the fluctuations of outer environment and inner environment, metabolism, and so on. In recent years, the research of the protein protein interaction networks has become one of core fields in proteomics.Biologists want to know the function of each protein, involving in which cell circuits and the exact position on the cell circuits. In this thesis, based on investigating the structural properties of budding yeast, we proposed a markov model for the evolution of yeast protein interaction networks. In our model, the interaction probability between two proteins proportional to sum number of the surface hydrophobic residues, the stochasticity arised by various fluctuations which are inevitable in living world is controlled by a temperature-like parametera . At last, we get the probability of each protein involving the physiological processes in the budding yeast cell.