Understanding the complex structure of gene regulation, gene regulatory networks, and how those networks are altered in disease- and tissue- specific contexts, are all critical for developing effective, precision-medicine based therapeutic strategies. In addition, integrating multi-Omics data to effectively model biological networks has the potential to provide unprecedented insights into the mechanisms underlying disease. Along these lines, our group has developed a suite of computational approaches that support: (1) effectively integrating multi-Omic data to model gene regulatory networks; (2) performing network analysis to identify the biological mechanisms mediating changes in disease state; and (3) modeling patient-specific networks in order to link regulatory alterations with heterogeneous disease phenotypes in order to support precision medicine. In this talk, I will review several specific applications in which we have used these methods to discover new features of disease and to understand the complex regulatory processes at work across patients.