Operator Norm Optimization for Structural Changes in Cryo-EM ImagingMS24

When taking Cryo-EM images of 3D protein structures, we obtain extremely noisy 2D images. Moreover, it is possible for the same proteins to have different forms under certain circumstances. We want to discuss how to describe such different forms of the same proteins by the unknown covariance matrix representing 3D conformational changes. Since we are most interest in the major deviation in the change, we look for the first principal component via operator norm optimization.

This presentation is part of Minisymposium “MS24 - Data-driven approaches in imaging science (3 parts)
organized by: Jae Kyu Choi (Institute of Natural Sciences, Shanghai Jiao Tong University) , Chenglong Bao (Yau Mathematical Sciences Center, Tsinghua University) .

Yunho Kim (Department of Mathematical Sciences, Ulsan National Institute of Science and Technology)
image reconstruction, inverse problems, nonlinear optimization