Event Location: Newell Simon Hall 1507
Bio: Dr. Min Xu is an Assistant Research Professor of Computational Biology at the Computational Biology Department in the School of Computer Science at Carnegie Mellon University. He received degrees in Computational Biology, Computer Science, and Applied Mathematics. He has more than 16 years of research experience in various Computational Biology areas. His current research focus on Cellular Electron CryoTomography 3D image derived modelling of cell organization at molecular resolution.

Abstract: The cell is the basic structural and functional unit of all living organisms. Inside a cell, macromolecular complexes are nanomachines that participate in a wide range of processes. The recent revolutions in Electron CryoTomography enables 3D visualization of cell organization in a near native state at molecular resolution. The produced 3D images provide detailed information about all macromolecular complexes, their structures, their abundances, and their specific spatial locations and orientations inside the field of view. However, extracting this information is very challenging and current methods usually rely on templates of known structure. Here, we formulate a template-free structural analysis as a pattern mining problem and propose a new framework called “Multi Pattern Pursuit” for supporting de novo discovery of macromolecular complexes in cellular tomograms without using templates of known structures. Our tests on simulated and experimental tomograms show that our method is a promising tool for such analysis.