Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Cryo-electron Microscopy01:28

Cryo-electron Microscopy

3.7K
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...
3.7K
Electron Microscope Tomography and Single-particle Reconstruction01:07

Electron Microscope Tomography and Single-particle Reconstruction

2.6K
Transmission electron microscopy (TEM) can be used to determine the 3D structure of biological samples with the help of techniques such as electron microscope tomography and single-particle reconstruction. While single-particle reconstruction can examine macromolecules and macromolecular complexes in vitro conditions only, tomography permits the study of cell components or small cells in vivo.
Electron Tomography
Electron tomography can be performed either in TEM or STEM (scanning transmission...
2.6K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Structure of the bacteriophage PhiKZ non-virion RNA polymerase bound to a p119L open promoter analogue.

IUCrJ·2025
Same author

Uncovering synaptic and cellular nanoarchitecture of brain tissue via seamless <i>in situ</i> trimming and milling for cryo-electron tomography.

bioRxiv : the preprint server for biology·2025
Same author

Outcomes of the EMDataResource cryo-EM Ligand Modeling Challenge.

Nature methods·2024
Same author

Outcomes of the EMDataResource Cryo-EM Ligand Modeling Challenge.

Research square·2024
Same author

MRC2020: improvements to Ximdisp and the MRC image-processing programs.

IUCrJ·2023
Same author

Cryo-EM single-particle structure refinement and map calculation using Servalcat.

Acta crystallographica. Section D, Structural biology·2021

Related Experiment Video

Updated: Oct 5, 2025

A Robust Single-Particle Cryo-Electron Microscopy cryo-EM Processing Workflow with cryoSPARC, RELION, and Scipion
13:43

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

Published on: January 31, 2022

14.0K

Real space in cryo-EM: the future is local.

Colin M Palmer1, Christopher H S Aylett2

  • 1Scientific Computing Department, Science and Technology Facilities Council, Research Complex at Harwell, Didcot OX11 0FA, United Kingdom.

Acta Crystallographica. Section D, Structural Biology
|February 1, 2022
PubMed
Summary

Cryo-electron microscopy (cryo-EM) image processing faces noise challenges. New real-space methods, incorporating local variations and prior information, offer improved signal recovery over traditional Fourier-space approaches for better macromolecular structure determination.

Keywords:
cryo-EMdenoisinglocal filteringlocal resolutionnoise suppressionreal-space filteringreal-space measures

More Related Videos

Single Particle Cryo-Electron Microscopy: From Sample to Structure
11:52

Single Particle Cryo-Electron Microscopy: From Sample to Structure

Published on: May 29, 2021

8.9K
Cryo-EM and Single-Particle Analysis with Scipion
09:06

Cryo-EM and Single-Particle Analysis with Scipion

Published on: May 29, 2021

4.0K

Related Experiment Videos

Last Updated: Oct 5, 2025

A Robust Single-Particle Cryo-Electron Microscopy cryo-EM Processing Workflow with cryoSPARC, RELION, and Scipion
13:43

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

Published on: January 31, 2022

14.0K
Single Particle Cryo-Electron Microscopy: From Sample to Structure
11:52

Single Particle Cryo-Electron Microscopy: From Sample to Structure

Published on: May 29, 2021

8.9K
Cryo-EM and Single-Particle Analysis with Scipion
09:06

Cryo-EM and Single-Particle Analysis with Scipion

Published on: May 29, 2021

4.0K

Area of Science:

  • Structural Biology
  • Biophysics
  • Computational Biology

Background:

  • Cryo-electron microscopy (cryo-EM) yields low signal-to-noise ratio (SNR) images due to radiation sensitivity and poor contrast of biological macromolecules.
  • Current cryo-EM image processing relies on averaging, parameter optimization, and prior information, but struggles with parameter estimation, overfitting, and signal variations.
  • Traditional Fourier-space methods have limitations in handling local variations inherent in biological samples.

Purpose of the Study:

  • To propose and evaluate novel image processing strategies for cryo-EM that better address the local nature of biological samples.
  • To improve the reliability and accuracy of macromolecular structure determination from low-SNR cryo-EM data.
  • To explore the integration of real-space and Fourier-space approaches for enhanced cryo-EM image processing.

Main Methods:

  • Development of real-space measures and filters that account for local variations within cryo-EM images and volumes.
  • Application of band-pass filtered real-space volumes and striding resolution through Fourier space.
  • Exploration of incorporating powerful prior information, such as from AlphaFold, within real-space processing frameworks.

Main Results:

  • Real-space measures are demonstrated to be more reliable and appropriate for biological samples than global Fourier-space measures.
  • Proposed hybrid real-space/Fourier-space methods are expected to outperform global Fourier-space-based approaches.
  • Locality in image processing, through real-space operations, is identified as a central theme for future cryo-EM advancements.

Conclusions:

  • Real-space processing offers significant advantages for cryo-EM by addressing local sample variations and enabling novel prior information integration.
  • A combination of real-space operations on frequency bands and striding resolution offers a promising direction for improved cryo-EM image processing.
  • Future cryo-EM image processing will likely integrate real-space locality with advanced computational methods, including deep learning and structural prediction tools.