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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: Oct 10, 2025

A Robust Single-Particle Cryo-Electron Microscopy cryo-EM Processing Workflow with cryoSPARC, RELION, and Scipion

A Robust Single-Particle Cryo-Electron Microscopy cryo-EM Processing Workflow with cryoSPARC, RELION, and Scipion

Published on: January 31, 2022

Cloud computing platforms to support cryo-EM structure determination.

Yilai Li¹, Michael A Cianfrocco¹

¹Life Sciences Institute & Department of Biological Chemistry, University of Michigan, Ann Arbor, MI, USA.

Trends in Biochemical Sciences

|December 13, 2021

Summary

Single-particle cryo-electron microscopy (cryo-EM) needs strong computational resources. This work explores cloud computing for cryo-EM, proposing a hybrid workflow to improve accessibility and integration.

Keywords:

cloud computing cryo-EM

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Last Updated: Oct 10, 2025

A Robust Single-Particle Cryo-Electron Microscopy cryo-EM Processing Workflow with cryoSPARC, RELION, and Scipion

A Robust Single-Particle Cryo-Electron Microscopy cryo-EM Processing Workflow with cryoSPARC, RELION, and Scipion

Published on: January 31, 2022

Author Spotlight: Enhancing Cryo-Electron Microscopy by Automated Data Collection and Analysis Techniques

Author Spotlight: Enhancing Cryo-Electron Microscopy by Automated Data Collection and Analysis Techniques

Published on: December 1, 2023

Single Particle Cryo-Electron Microscopy: From Sample to Structure

Single Particle Cryo-Electron Microscopy: From Sample to Structure

Published on: May 29, 2021

Area of Science:

Structural Biology
Computational Biology
Biophysics

Background:

Single-particle cryo-electron microscopy (cryo-EM) is a powerful technique for determining protein structures at near-atomic resolution.
The increasing demand for cryo-EM data processing necessitates scalable and accessible computational infrastructure.
Current computational resources may present bottlenecks for widespread adoption and advanced analysis.

Purpose of the Study:

To review the current cloud computing landscape relevant to cryo-electron microscopy.
To envision a hybrid computational workflow integrating cloud and local resources for cryo-EM.
To provide recommendations for the cryo-EM community to facilitate cloud integration.

Main Methods:

Review of existing cloud computing platforms and services.
Analysis of the requirements for cryo-EM data processing pipelines.
Conceptualization of a hybrid computing model combining on-premises and cloud resources.

Main Results:

The cloud computing landscape offers diverse solutions for scalable cryo-EM data processing.
A hybrid workflow can balance computational demands, cost-effectiveness, and data security.
Key considerations for implementation include data transfer, software compatibility, and cost management.

Conclusions:

Cloud computing presents a viable and scalable solution to meet the growing computational demands of cryo-EM.
A hybrid approach offers flexibility and efficiency for cryo-EM workflows.
Community adoption of cloud-integrated workflows will enhance the accessibility and impact of cryo-EM.