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bioRxiv · 10.1101/2024.11.04.621604

A comprehensive foundation model for cryo-EM image processing

Yan, Y.·Fan, S.·Yuan, F.·Shen, H.
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Abstract

Cryogenic electron microscopy (cryo-EM) has become a premier technique for high-resolution structural determination of biological macromolecules1-4. However, its widespread adoption is hampered by the need for specialized expertise. We introduce the Cryo-EM Image Evaluation Foundation (Cryo-IEF) model, pre-trained on an extensive dataset of approximately 65 million cryo-EM particle images using unsupervised learning. Cryo-IEF excels in various cryo-EM data processing tasks, such as classifying particles from different structures, clustering particles by pose, and assessing the quality of particle images. Upon fine-tuning, the model effectively ranks particle images by quality at high efficiency, enabling the creation of CryoWizard--a fully automated single-particle cryo-EM data processing pipeline. This pipeline has successfully resolved high-resolution structures of diverse properties and proven adept at mitigating the prevalent preferred orientation challenge in many cryo-EM samples. The Cryo-IEF model and CryoWizard pipeline collectively represent a significant advancement in rendering cryo-EM technology more accessible, efficient, and robust, with substantial implications for life sciences research.

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Yan, Y., Fan, S., Yuan, F., Shen, H.. 2024-11-06. A comprehensive foundation model for cryo-EM image processing. https://doi.org/10.1101/2024.11.04.621604

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