| In this dissertation, statistical mechanics, graph theory, and machine learning methods have been used to study the topology, modularity, organization and robustness of the protein-protein interaction network of budding yeast Saccharomyces cerevisiae. The protein-protein interaction dataset is obtained by combining high confidence interactions, and is validated from multiple perspectives. Statistical mechanics is then used to analyze the connectivity distribution, graph spectrum, shortest path distance and clustering coefficients of the network, which indicates that the network is both scale-free and modular. Microarray gene expression profiles are used to compute the weight for each interaction and the network is represented as a weighted undirected graph. An edge betweenness-based algorithm is developed and applied on the graph, and a set of functional modules is identified in the network. The functional modules are then validated rigorously against gene annotation, growth phenotype and protein complexes. It is found that genes in the same functional module exhibit similar deletion phenotype, and that known protein complexes are largely contained in the functional modules. To find out the organizations of the yeast proteome network, the relationship between the gene expression profiles of hubs and their interacting proteins is analyzed. The results indicate that subpopulations of hubs exist in the yeast proteome network, which are classified as type core, local and global hubs. By examining these hub populations from the perspectives of protein complexes, interaction overlap, clustering coefficients, module connectivity, and visualization, it is found that global hubs form the backbone of module-module interaction, while core hubs are organizers within functional modules. In addition, analysis on the interactions between the hubs indicated that each of the three types of hubs preferentially interact with hubs from the same population, which suggests an ordered architecture for the network and the existence of central processing subnetwork at both global and functional module level. Gene expression changes of the hub populations in cellular responses are then analyzed to gain insights into the dynamics of module-module interactions, and the results suggest that global hubs are the major and early responders in cellular response. Next, network breakdown simulation and graph spectrum are used to examine the contributions of each hub population to the robustness of the yeast proteome network. The results indicate that network organizers contribute most to the robustness at both global and local levels. And last, it is found that genes contributing most to the robustness of functional modules, not that of the entire network, are more likely to be essential. |
