## Image registration, classification and averaging in cryo-electron tomography

- March 24, 2009
- 3:30 p.m.
- Sumwalt 102

## Abstract

Cryo-electron tomography provides opportunities to determine three-dimensional cellular architecture at resolutions high enough to identify individual macromolecules such as proteins. Image analysis of such data poses a challenging problem due to the extremely low signal-to-noise ratios that makes individual volumes simply too noisy to allow reliable structural interpretation. Complex entities such as cells and viruses, nevertheless, contain multiple copies of numerous macromolecules that can individually be subjected to 3D averaging to boost the signal-to-noise ratios and allow meaningful interpretation. The problem can be casted within a mathematical framework of joint 3D image alignment and classification that is both interesting and challenging. I will report progress in addressing some of these challenges which involve dealing with missing data, the need for robust and computationally efficient 3D image registration routines, and the design of methods that account for conformational diversity through the use of clustering techniques. I will also present some recent developments on structural studies of the HIV virus empowered by the mathematical and computational artillery we have developed.