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.
Kimberly Glass is an expert in complex networks and genomic data analysis. She obtained her PhD in Physics in 2010 from the University of Maryland. From 2010-2014, Dr. Glass was a postdoctoral fellow at Dana-Farber Cancer Institute and the Harvard T.H. Chan School of Public Health where she received training in computational biology. During her post-doc she developed several computational and data-integration methods for inferring and analyzing gene regulatory networks. In 2014 Kimberly joined the faculty of the Channing Division of Network Medicine (CDNM) at Brigham and Women’s Hospital where she is continuing her research in systems medicine and network methods. Her current research focuses on how to integrate and interpret multiple biological data-types in the regulatory network context and on how to understand the biological mechanisms represented in these networks. She is also investigating potential applications of networks in precision medicine, using network approaches to understand susceptibility to, severity, and treatment of complex diseases.
Kimberly Glass is an expert in complex networks and genomic data analysis. She obtained her PhD in Physics in 2010 from the University of Maryland. From 2010-2014, Dr. Glass was a postdoctoral fellow at Dana-Farber Cancer Institute and the Harvard T.H. Chan School of Public Health where she received training in computational biology. During her post-doc she developed several computational and data-integration methods for inferring and analyzing gene regulatory networks. In 2014 Kimberly joined the faculty of the Channing Division of Network Medicine (CDNM) at Brigham and Women’s Hospital where she is continuing her research in systems medicine and network methods. Her current research focuses on how to integrate and interpret multiple biological data-types in the regulatory network context and on how to understand the biological mechanisms represented in these networks. She is also investigating potential applications of networks in precision medicine, using network approaches to understand susceptibility to, severity, and treatment of complex diseases.
