A self-supervised workflow for particle picking in cryo-EM

McSweeney, Donal M.; McSweeney, Sean M.; Liu, Qun

doi:10.1107/S2052252520007241

Title: A self-supervised workflow for particle picking in cryo-EM

Journal Article · 22 June 2020 · IUCrJ

DOI: https://doi.org/10.1107/S2052252520007241 · OSTI ID:1633026

McSweeney, Donal M. ^[1];

^[1];

^[1]

Brookhaven National Lab. (BNL), Upton, NY (United States)

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.

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Research Organization:: Brookhaven National Laboratory (BNL), Upton, NY (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: SC0012704

OSTI ID:: 1633026

Alternate ID(s):: OSTI ID: 1634176

Report Number(s):: BNL--216002-2020-JAAM

Journal Information:: IUCrJ, Journal Name: IUCrJ Journal Issue: 4 Vol. 7; ISSN 2052-2525; ISSN IUCRAJ

Publisher:: International Union of CrystallographyCopyright Statement

Country of Publication:: United States

Language:: English

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Related Subjects

59 BASIC BIOLOGICAL SCIENCES
cryo-EM
particle picking
particle improvement
2D class averages
convolutional neural network (CNN)
automation
deep learning

Title: A self-supervised workflow for particle picking in cryo-EM

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