Please join us for a UW Data Science Seminar event on Tuesday, October 13th from 4:30 to 5:30 p.m. The seminar will feature Dong Si, Assistant Professor of Computing and Software Systems at UW Bothell as he presents “Fast, Accurate, and Fully Automated Protein Complex Structure Prediction from 3D Cryo-EM and Sequence.”
Please use this zoom link for the event.
Abstract: Information about macromolecular structure of protein complexes such as viral proteins in SARS-CoV-2, and related cellular and molecular mechanisms can assist the search for vaccines and drug development processes. To obtain such structural information, we present DeepTracer, a fully automatic deep learning-based method for fast de novo multi-chain protein complex structure determination from high-resolution cryo-electron microscopy (cryo-EM) density maps. We applied DeepTracer on a set of coronavirus-related density maps, some even with no deposited structure available in EMDataResource. Additional tests with related state-of-the-art methods further exemplify DeepTracer’s competitive accuracy and efficiency of structure modeling. DeepTracer allows for exceptionally fast computations, making it possible to trace around 60,000 residues in 350 chains within only two hours. The web service is globally accessible at https://deeptracer.uw.edu.
Dr. Dong Si is currently an Assistant Professor at University of Washington Bothell and the Principal Investigator of Data Analysis & Intelligent Systems (DAIS) research group. He received his M.S. and Ph.D. in Computer Science from Old Dominion University, and his B.S. in Electronic Information Science from Nanjing University. Over the years, Dong’s research has included feature detection and pattern recognition, machine learning and artificial intelligence, and biomedical informatics.
Dr. Dong Si’s research interest is mainly focused on developing and applying machine learning and artificial intelligence techniques to solve biomedical and health science problems, such as biomedical image processing, protein structure predictions, behavioral and mental health data analysis. In addition, he is interested in promoting early engagement of undergraduate students (especially women and underrepresented students) in machine learning, biomedical informatics, and data science field by introducing interdisciplinary studies, and inspiring students to pursue advanced STEM education and research careers.
The UW Data Science Seminar is an annual lecture series at the University of Washington that hosts scholars working across applied areas of data science, such as the sciences, engineering, humanities and arts along with methodological areas in data science, such as computer science, applied math and statistics. Our presenters come from all domain fields and include occasional external speakers from regional partners, governmental agencies and industry.
All seminars will be hosted virtually for the 2020-2021 academic year, and are free and open to the public.