Georgia Tech SCL Georgia Tech SCL Georgia Tech SCL

Title: Computational Regulatory Genomics

Abstract:

Gene regulation refers to how genes in a cell are switched on or off to determine a cell’s fate and function. It is central to an extraordinary range of biological phenomena from development to disease, as well as the evolution of diverse life forms. My group’s research develops and uses computational tools, based on probabilistic inference, machine learning, and biophysics-inspired models, to answer unsolved and topical questions related to gene regulation in diverse biological processes.

Scientists today use diverse high-throughput technologies to generate “multi-omics” (genomics, transcriptomics, metabolomics, etc.) data that provide detailed views of a biological process from different vantage points. We develop principled approaches to analyze these multi-omics data in an integrated manner and uncover regulatory mechanisms underlying the process, including key regulators and networks of regulatory interactions. Another major direction of our research is to decipher “the cis-regulatory code”, i.e., to precisely describe how gene regulation is encoded in DNA as so-called regulatory elements. It is estimated that 90% of known disease-related mutations may be located in these regulatory elements, necessitating quantitative models that can accurately predict their function and the impact of mutations therein. In this talk, I will show how our analytical tools can provide experimentally testable hypotheses regarding regulatory networks and the function of regulatory elements, in the context of development, behavior, cancer progression, and drug response. I will also outline major directions for our future research.

Bio:

Saurabh Sinha received his Ph.D. in Computer Science from the University of Washington, Seattle, in 2002, and after post-doctoral work at the Rockefeller University with Eric Siggia, he joined the faculty of the University of Illinois, Urbana-Champaign, in 2005. He is Founder Professor and Willett Faculty Scholar in the Department of Computer Science, and Director of Computational Genomics in the Carl R. Woese Institute for Genomic Biology. His research is in the area of bioinformatics, with a focus on regulatory genomics and systems biology. Sinha is an NSF CAREER award recipient and has been funded by NIH, NSF and USDA. He co-directed an NIH BD2K Center of Excellence and is currently a thrust lead in the NSF AI Institute at UIUC. He leads the educational program of the Mayo Clinic-University of Illinois Alliance, and co-led data science education for the Carle Illinois College of Medicine. Sinha has served as Program co-Chair of the annual RECOMB Regulatory and Systems Genomics conference and is on the Board of Directors for the International Society for Computational Biology. He was a recipient of the University Scholar award of the University of Illinois, and selected as a Fellow of the AIMBE in 2018.