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Cryo-electron Microscopy

Cryo-electron Microscopy

Conventional electron microscopy (EM) involves dehydration, fixation, and staining of biological samples, which distorts the native state of biological molecules and results in several artifacts. Also, the high-energy electron beam damages the sample and makes it difficult to obtain high-resolution images. These issues can be addressed using cryo-EM, which uses frozen samples and gentler electron beams. The technique was developed by Jacques Dubochet, Joachim Frank, and Richard Henderson, for...

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Related Experiment Video

Updated: Jan 10, 2026

Routine Collection of High-Resolution cryo-EM Datasets Using 200 KV Transmission Electron Microscope

Routine Collection of High-Resolution cryo-EM Datasets Using 200 KV Transmission Electron Microscope

Published on: March 16, 2022

A comprehensive foundation model for cryo-EM image processing.

Yang Yan^1,2, Shiqi Fan^1,2, Fajie Yuan^3,4

¹Research Center for Industries of the Future, Westlake University, Hangzhou, China.

|November 27, 2025

Summary

This summary is machine-generated.

Cryo-EM Image Evaluation Foundation (Cryo-IEF) model automates cryo-EM processing, making high-resolution structure determination more accessible. CryoWizard pipeline uses Cryo-IEF to overcome expertise barriers and solve complex sample structures.

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Related Experiment Videos

Last Updated: Jan 10, 2026

Routine Collection of High-Resolution cryo-EM Datasets Using 200 KV Transmission Electron Microscope

Routine Collection of High-Resolution cryo-EM Datasets Using 200 KV Transmission Electron Microscope

Published on: March 16, 2022

Single Particle Cryo-Electron Microscopy: From Sample to Structure

Single Particle Cryo-Electron Microscopy: From Sample to Structure

Published on: May 29, 2021

Strategies for Optimization of Cryogenic Electron Tomography Data Acquisition

Strategies for Optimization of Cryogenic Electron Tomography Data Acquisition

Published on: March 19, 2021

Area of Science:

Structural Biology
Biophysics
Computational Biology

Background:

Cryo-electron microscopy (cryo-EM) is crucial for high-resolution macromolecular structure determination.
Specialized expertise is a significant barrier to broader cryo-EM application.

Purpose of the Study:

Introduce the Cryo-EM Image Evaluation Foundation (Cryo-IEF) model to democratize cryo-EM.
Develop CryoWizard, an automated processing pipeline using Cryo-IEF for efficient structure determination.

Main Methods:

Unsupervised learning on ~65 million cryo-EM particle images to pre-train the Cryo-IEF model.
Fine-tuning Cryo-IEF for particle quality ranking within the CryoWizard pipeline.
Applying CryoWizard to diverse biological samples for automated structure resolution.

Main Results:

Cryo-IEF demonstrates versatility in particle classification, pose-based clustering, and image quality assessment.
CryoWizard successfully resolves high-resolution structures from various sample types.
The pipeline effectively addresses the challenge of preferred orientation in cryo-EM data.

Conclusions:

The Cryo-IEF model and CryoWizard pipeline significantly lower the expertise threshold for cryo-EM.
Automated processing enhances efficiency and accessibility for determining complex biological structures.
This approach broadens the applicability of cryo-EM in structural biology research.