Computational methods for integrating and analyzing human systems biology data

摘要

The combination of heterogeneous biological datasets is a key requirement for modern molecular systems biology. Of particular importance for our understanding of complex biological systems like the human cell are data about the interactions of proteins with other molecules. In this thesis, we develop and apply methods to improve the availability and the quality of such interaction data. We also demonstrate how these data can be used in interdisciplinary studies to discover new biological results. First, we develop technical systems for the instant integration of interaction data that are stored and maintained in separate online repositories. Second, we implement a computational framework for the application of multiple scoring algorithms to qualitatively assess different aspects of interaction data. Our methods are based on distributed client-server systems, ensuring that the services can be updated continuously. This promotes equal access to interaction data and allows researchers to expand the client-server systems with their own service. Third, we focus our application studies on integrative network-based analyses of human host factors for viral infections. Our applications provide new biological insights into the life cycle of the hepatitis C virus and identify new potential candidates for antiviral drug therapy.