Cryo-electron microscopy (cryo-EM) is a technique for three-dimensional imaging of biological macromolecules. Molecules are frozen in a thin layer of ice and their tomographic projections are recorded in an electron microscope. Recent advances have yielded molecular reconstructions at near-atomic resolution, and in 2017 the Nobel Prize in Chemistry was awarded to three pioneers of the field. The goal of this minisymposium is to bring together the communities of cryo-EM and computational imaging to facilitate the exchange of new ideas and perspectives. It will cover fast algorithms for reconstruction, resolving high-resolution structures, validation, structural variability in heterogeneous samples, and other topics.

Overview of computational challenges in cryo-EM analysis

Amit Singer (Princeton University)

Atomic resolution single particle Cryo-EM

Alberto Bartesaghi (CCR/NCI/NIH)

Viewing direction estimation for molecules with rotational symmetry

Gabi Pragier (Tel Aviv University)

Resolution measures in Electron Microscopy reconstructions

Carlos Oscar Sorzano (Centro Nacional Biotecnología)

Manifold denoising for cryo-EM data sets

Yoel Shkolnisky (Tel Aviv University)

Toward single particle reconstruction without particle picking: Breaking the detection limit

Tamir Bendory (Princeton University)

Multi-Reference Factor Analysis - MRFA

Yariv Aizenbud (Tel Aviv University)

3D ab initio modeling in cryo-EM by autocorrelation analysis

Eitan Levin (Princeton University)

Resolving cryo-EM heterogeneity with low-rank methods

Joakim Andén (Flatiron Institute)

Organizers:

Joakim Andén (Flatiron Institute)

Roy Lederman (Yale University)

Keywords:

bayesian methods, computed tomography, cryo-em, image reconstruction, image registration, inverse problems, machine learning