Cryogenic electron microscopy (cryo-EM) has become widely used for the past few years to find the 3D structure of biomolecules and identify their multiple conformational states, as a set of 3D volumes, also called EM maps. I will present several recent computational methods and bioinformatic tools applied to cryo-EM data, with a specific focus on the study of the ribosome structure, which is the RNA-protein complex that mediates protein translation. In a first part, I’ll present how we developed tools to extract and visualize the geometric properties of the ribosome to compare structures across the PDB database. In the second part, I will introduce a bioinformatic tool that interpolates and generates morphing trajectories joining two given EM maps. These interpolants are built using recent advances in computational optimal transport, to notably allow efficient evaluation of Wasserstein barycenters of 3D shapes. I will show how the method performs on experimental data, with significant improvement over existing methods. Furthermore, I'll describe how this transport-based approach can be applied to other biological contexts and computational problems, e.g. for fast alignment of 3D EM maps, and interpolation and classification of cell shapes.
Khanh Dao Duc an Assistant Professor in the Department of Mathematics at the University of British Columbia, and an associate member of the Departments of Computer Science and Zoology. Dr. Dao Duc's research group combines mathematical, computational, and statistical tools to study fundamental biological processes (for more details, see his publications). We are currently mostly focusing on studying the properties of the ribosome across scales and systems (NSERC Discovery grant RGPIN-2020-05348), and developing new algorithms for Cryo-EM data (New Frontiers of Research NFRFE-2019-00486). CV is available here.
Faculty Host: Oana Carja (CMU)
Zoom Participation. See announcement.