Computer Sciences Colloquium - Challenges and opportunities in cross-omic analysis of the human microbiome

Abstract:

The human microbiome – the complex ensemble of microorganisms that populate the human body – represents a vastly complex ecosystem that is tightly linked to our health. Multiple molecular assays now enable high-throughput profiling of this system, providing large-scale and comprehensive characterization of its ecology, functional capacity, and metabolic activity. To date, however, analyses of such multi-omic data typically focus on statistical associations, often ignoring extensive prior knowledge of the mechanisms, dependencies, and regularities linking these various facets of the microbiome. In this talk, I will highlight the pressing need for the development of systems-level and model-based methods for integrating microbiome-derived multi-omic data and will introduce several novel computational frameworks for linking taxonomic, genomic, metagenomic, and metabolomic information about the microbiome. Combined, such frameworks lead to an improved comprehensive, multi-scale, and mechanistic understanding of the microbiome in health and disease, informing efforts for personalized microbiome-based therapy.

Brief Bio:

​Elhanan Borenstein is an associate professor of Genome Sciences at the University of Washington, with an adjunct position in the Department of Computer Science and engineering. He is also an external professor at the Santa Fe Institute for complexity science. Dr. Borenstein received his PhD in computer science from Tel-Aviv University, Israel, and held a joint postdoctoral fellowship at the Department of Biology in Stanford and at the Santa Fe Institute. He also has extensive professional experience in the hi-tech industry, where he held top management positions in several hi-tech companies. Dr. Borenstein integrates metagenomic data with methods inspired by systems biology, network theory, machine-learning, and statistical inference to develop a variety of computational methods for studying the human microbiome. His work focuses on reconstructing predictive, systems-level models of the human microbiome and on integrative, multi-meta-omic analysis, aiming to provide a better principled understanding of the microbiome and its role in human health. Dr. Borenstein is the recipient of various awards including, most recently, the Alfred P. Sloan Fellowship and the NIH New Innovator Award.