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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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Updated: Jun 30, 2025

Cryo-EM and Single-Particle Analysis with Scipion

Cryo-EM and Single-Particle Analysis with Scipion

Published on: May 29, 2021

Scipion3: A workflow engine for cryo-electron microscopy image processing and structural biology.

Pablo Conesa¹, Yunior C Fonseca¹, Jorge Jiménez de la Morena¹

¹National Center of Biotechnology (CNB-CSIC), Madrid, Spain.

Biological Imaging

|March 21, 2024

Summary

This summary is machine-generated.

Scipion is a new Python-based workflow engine designed for complex image processing tasks, particularly in cryo-electron microscopy single-particle analysis (cryo-EM SPA). It enhances traceability and reproducibility for scientific image data analysis.

Keywords:

cryo-EM extensible integration multidomain software-framework workflows

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Last Updated: Jun 30, 2025

Cryo-EM and Single-Particle Analysis with Scipion

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High-resolution Single Particle Analysis from Electron Cryo-microscopy Images Using SPHIRE

High-resolution Single Particle Analysis from Electron Cryo-microscopy Images Using SPHIRE

Published on: May 16, 2017

Area of Science:

Computational Biology
Biophysics
Microscopy

Background:

Image processing pipelines, especially in cryo-electron microscopy single-particle analysis (cryo-EM SPA), involve complex, multi-step workflows.
Obtaining 3D structures requires processing millions of images from thousands of micrographs, demanding robust workflow management.
Low signal-to-noise ratio (SNR) in cryo-EM data leads to significant estimation errors, complicating analysis.

Purpose of the Study:

To introduce Scipion, a generic, open-source, Python-based workflow engine tailored for image processing.
To address the challenges of managing complex workflows, ensuring traceability, and improving reproducibility in scientific image analysis.

Main Methods:

Scipion is a workflow engine developed in Python, featuring a smart object model and designed for interoperability.
It supports execution in streaming, integration with high-performance computing, and offers flexible visualization and scripting capabilities.
The engine includes features for traceability, reproducibility, self-reporting, reusability, extensibility, and user authentication.

Main Results:

Scipion provides a comprehensive solution for managing intricate image processing workflows, particularly in cryo-EM SPA.
Key features include interoperability, a smart object model, gluing and comparison operations, and domain-specific operations.
The engine is designed for high performance, enabling execution with or without graphical capabilities and smooth integration into HPC environments.

Conclusions:

Scipion offers a powerful, flexible, and reproducible platform for scientific image processing, enhancing the analysis of complex datasets.
Its generic nature and open-source, non-restrictive licensing make it adaptable to various biological imaging domains beyond cryo-EM.
The tool facilitates efficient data analysis, improves the reliability of results, and supports collaborative research through its advanced features.