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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: Sep 9, 2025

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

Magellon - an extensible platform for cryo-EM data visualization, management and processing.

Behdad Khoshbin¹, Puneeth Damodar¹, Rupali R Garje²

¹Institute of Molecular Biophysics, Florida State University, Tallahassee, FL, USA.

|September 5, 2025

Summary

This summary is machine-generated.

Magellon is a new software platform for single-particle cryo-electron microscopy (cryo-EM) that streamlines data processing and analysis. Its microservices architecture offers flexibility and scalability for researchers studying macromolecular structures.

Keywords:

Magellon automation cryo-EM data processing macromolecular structures structural biology

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Last Updated: Sep 9, 2025

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

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

Published on: December 1, 2023

Area of Science:

Structural Biology
Biophysics
Computational Biology

Background:

Single-particle cryo-electron microscopy (cryo-EM) is a powerful technique for determining high-resolution macromolecular structures.
Current cryo-EM workflows face challenges in data management, processing integration, and software extensibility.

Purpose of the Study:

To introduce Magellon, an innovative software platform designed to address the limitations of existing cryo-EM software.
To provide researchers with a flexible, scalable, and user-friendly solution for cryo-EM data processing and analysis.

Main Methods:

Development of Magellon, a cryo-EM software platform utilizing a microservices architecture.
Integration of an extensible backend with a web-based frontend (Magellon Viewer).
Implementation of a plugin-based architecture, distributed processing, monitoring systems, and novel data organization/visualization.

Main Results:

Magellon offers a unified platform for efficient cryo-EM data processing and analysis.
The platform combines high-performance computing with an intuitive user interface.
Key features include flexibility in computational resource selection, scalability, and extensibility.

Conclusions:

Magellon represents a significant advancement in cryo-EM software infrastructure.
The platform enhances ease of use, flexibility, and scalability for structural biology research.
Magellon empowers researchers to efficiently process and analyze complex cryo-EM datasets.