Remo Rohs: Structure-based deep learning models for predicting protein-DNA binding specificity

Speaker:

Remo Rohs (Department of Quantitative and Computational Biology, University of Southern California, Los Angeles)

Title:

Structure-based deep learning models for predicting protein-DNA binding specificity

Abstract:

Research in molecular biology has become increasingly quantitative and computational. This trend is due to two major drivers: Biology now generates large amounts of data in every experiment, and the power of computers has grown exponentially. The combination of data and computing is the basis for the recent development of AI-based computational biology methods. My lab develops such tools based on molecular structure with the goal to answer biological questions related to gene regulation, nucleic acid structure, protein-nucleic acid binding, and drug design. In my talk, I will discuss DeepPBS, a method for the prediction of protein-DNA binding specificity from structural data, and DrugHIVE, an approach for the design of drug-like molecules that are not available in current drug libraries. I will further introduce tools that my lab developed for the analysis and prediction of DNA and RNA structure and protein-nucleic acid binding.

Bio:

Remo Rohs is a professor of quantitative and computational biology, chemistry, physics and astronomy, computer science, medicine and biomedical engineering at the University of Southern California in Los Angeles, California. He received his undergraduate degree in physics at Humboldt University Berlin. His Ph.D. in chemistry is from Free University Berlin and the Max Delbrück Center for Molecular Medicine in Berlin, Germany. Rohs received postdoctoral training in structural biology at the Weizmann Institute of Science in Israel and further training in computational biology as research scientist at Columbia University in New York. Rohs started his independent faculty career at the University of Southern California in 2010, where he is a full professor since 2016. He is the founding chair of the Department of Quantitative and Computational Biology since 2021. Rohs is an Alfred P. Sloan Research Fellow, an elected Fellow of the American Association for the Advancement of Science (AAAS), the International Society for Computational Biology (ISCB), the Asia-Pacific Artificial Intelligence Association (AAIA), and an elected Member of the National Academy of Artificial Intelligence (NAAI).