The structure and function of biological networks

Biology has been revolutionized in recent years by an explosion in the availability of data. Transforming this new wealth of data into meaningful biological insights and clinical breakthroughs requires a complete overhaul both in the questions being asked and the methodologies used to answer them. A major challenge in organizing and understanding the data is the ability to define the structure in biological systems, especially high level structures. Networks are a powerful and versatile tool useful in bridging the data and the complex biological systems. To address the importance of the higher-level modular and hierarchical structure in biological networks, we have investigated in this thesis the topological structure of protein-protein interaction networks through a comprehensive network analysis using statistical and computational techniques and publicly available protein-protein interaction data sets. Furthermore, we have designed and implemented a novel and efficient computational approach to identify modules from a seed protein. The experiment results demonstrate the efficiency and effectiveness of this approach in finding a module whose members exhibit high functional coherency. In addition, toward quantitative studies of protein translation regulatory networks (PTRN), we have developed a novel approach to reconstruct the PTRN through integration of protein-protein interaction data and Gene Ontology annotations. We have applied computational techniques based on hierarchical random graph model on these reconstructed PTRN to explore their modular and hierarchical and to detect missing and false positive links from these networks. The identification of the high order structures in these networks unveils insights into their functional organization.Ph.D., Information Science and Technology -- Drexel University, 201