EMD-22026

Single-particle
2.4 Å
EMD-22026 Deposition: 21/05/2020
Map released: 05/08/2020
Last modified: 05/08/2020
Overview 3D View Sample Experiment Validation Volume Browser Additional data Links
Overview 3D View Sample Experiment Validation Volume Browser Additional data Links

EMD-22026

Reprocessing of EMPIAR-10218 data (20S proteasome) with particles picked by Kpicker

EMD-22026

Single-particle
2.4 Å
EMD-22026 Deposition: 21/05/2020
Map released: 05/08/2020
Last modified: 05/08/2020
Overview 3D View Sample Experiment Validation Volume Browser Additional data Links
Sample Organism: Thermoplasma acidophilum
Sample: 20S proteasome

Deposition Authors: McSweeney DM, McSweeney SM, Liu Q
A self-supervised workflow for particle picking in cryo-EM.
McSweeney DM, McSweeney SM , Liu Q
(2020) Iucrj , 7 , 719 - 727
PUBMED: 32695418
DOI: doi:10.1107/S2052252520007241
ISSN: 2052-2525
Abstract:
High-resolution single-particle cryo-EM data analysis relies on accurate particle picking. To facilitate the particle picking process, a self-supervised workflow has been developed. This includes an iterative strategy, which uses a 2D class average to improve training particles, and a progressively improved convolutional neural network for particle picking. To automate the selection of particles, a threshold is defined (%/Res) using the ratio of percentage class distribution and resolution as a cutoff. This workflow has been tested using six publicly available data sets with different particle sizes and shapes, and can automatically pick particles with minimal user input. The picked particles support high-resolution reconstructions at 3.0 Å or better. This workflow is a step towards automated single-particle cryo-EM data analysis at the stage of particle picking. It may be used in conjunction with commonly used single-particle analysis packages such as Relion, cryoSPARC, cisTEM, SPHIRE and EMAN2.