“Single-particle cryo-electron microscopy aims to determine the structure of 3D macromolecules from multiple 2D projections. Due to the high levels of noise, in conjunction with a distortion applied by the electron microscope, picking particle projections from the raw data outputted by the electron microscope is a challenging task. A second challenge is that a 3D volume reconstructed from the distorted projections may yield an unreliable representation of the macromolecule. It is therefore necessary to estimate the distortion applied by the electron-microscope to each of the picked projection images.

In this talk I will introduce a simple and novel approach for fast, accurate, and template-free particle  picking. This method, which can be considered as a mirror-image of pattern recognition, includes no model for the particle, and instead focuses on prior knowledge on the noise. I will also discuss a novel method for estimating the distortion applied by the electron-microscope, and include an evaluation of our methods on several publicly available datasets.”