ArticleActa crystallographica. Section F, Structural biology communications2025
CryoSift: an accessible and automated CNN-driven tool for cryo-EM 2D class selection.
Article in Acta crystallographica. Section F, Structural biology communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Article
- Helical reconstruction of amyloids in cryoSPARC.Acta crystallographica. Section F, Structural biology communications · 2026Article
- DM: a simple solution to suppress air-water interface interactions in cryo-EM.bioRxiv : the preprint server for biology · 2026Article
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9 authors.
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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. 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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