National Institutes of Health/National Institute of Biomedical Imaging and Bioengineering (NIH/NIBIB)
R01 GM143805
United States
Citation
Journal: Acta Crystallogr F Struct Biol Commun / Year: 2025 Title: CryoSift: an accessible and automated CNN-driven tool for cryo-EM 2D class selection. Authors: Jan Hannes Schäfer / Austin Calza / Keegan Hom / Puneeth Damodar / Ruizhi Peng / Nebojša Bogdanović / Gabriel C Lander / Scott M Stagg / Michael A Cianfrocco / Abstract: Single-particle cryo-electron microscopy (cryo-EM) has become an essential tool in structural biology. However, automating repetitive tasks remains an ongoing challenge in cryo-EM data-set processing. ...Single-particle cryo-electron microscopy (cryo-EM) has become an essential tool in structural biology. However, automating repetitive tasks remains an ongoing challenge in cryo-EM data-set processing. Here, we present a platform-independent convolutional neural network (CNN) tool for assessing the quality of 2D averages to enable the automatic selection of suitable particles for high-resolution reconstructions, termed CryoSift. We integrate CryoSift into a fully automated processing pipeline using the existing cryosparc-tools library. Our integrated and customizable 2D assessment workflow enables high-throughput processing that accommodates experienced to novice cryo-EM users.
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