Speaker
Description
Rapidly growing Omics data are providing an unprecedented opportunity to gain novel insights into biological systems and disease processes. Network modeling is a powerful approach that can be used to integrate complex information from multiple types of Omics data. In the field of network medicine, our group has developed a suite of methods that support: (1) effective integration of multi-omic data to reconstruct gene regulatory networks; (2) network analysis to identify changes in gene regulation between different biological systems or disease states; and (3) modeling of individual-specific networks in order to link regulatory alterations with heterogeneous phenotypes. In this talk, I will review several of these methods and describe specific applications in which we have used these approaches to understand the complex regulatory processes at work across different biological states, diseases, and individuals.
