Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

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...

Electron Microscope Tomography and Single-particle Reconstruction

Electron Microscope Tomography and Single-particle Reconstruction

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...

Two-Dimensional Microscopy in Microbiology

Two-Dimensional Microscopy in Microbiology

Two-dimensional (2D) microscopy encompasses a range of optical techniques that capture images within a single focal plane, offering detailed representations of microscopic structures. These techniques are essential in biological and medical research, enabling the visualization of cellular and subcellular structures with different levels of contrast and specificity.There are several major types of 2D microscopy, each with strengths and applications.Bright-Field MicroscopyBright-field microscopy...

You might also read

Related Articles

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

Sort by

Same author

Revealing Three-Dimensional Structure of an Individual Colloidal Crystal Grain by Coherent X-Ray Diffractive Imaging.

Physical review letters·2016

Same author

[Polypharmacy after Discharge from Hospital: An Analysis Using Data of the Statutory Health Insurance (AOK) of Saxony-Anhalt].

Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany))·2016

Same author

Improving the forecast for biodiversity under climate change.

Science (New York, N.Y.)·2016

Same author

Photoinduced Enhancement of the Charge Density Wave Amplitude.

Physical review letters·2016

Same author

A scientist's guide for submitting data to ZFIN.

Methods in cell biology·2016

Same author

[The role of reflectance confocal microscopy and optical coherence tomography in the diagnosis of epithelial-cystic conjunctival nevus].

Annales de dermatologie et de venereologie·2016

Same journal

Subspace Method of Moments for <i>Ab Initio</i> 3-D Single Particle Cryo-EM Reconstruction.

SIAM journal on imaging sciences·2026

Same journal

Smooth optimization using global and local low-rank regularizers.

SIAM journal on imaging sciences·2026

Same journal

A Common Lines Approach for Ab Initio Modeling of Molecules with Tetrahedral and Octahedral Symmetry.

SIAM journal on imaging sciences·2025

Same journal

A Wasserstein-Type Distance for Gaussian Mixtures on Vector Bundles with Applications to Shape Analysis.

SIAM journal on imaging sciences·2025

Same journal

On Learned Operator Correction in Inverse Problems.

SIAM journal on imaging sciences·2025

Same journal

Toward Single Particle Reconstruction without Particle Picking: Breaking the Detection Limit.

SIAM journal on imaging sciences·2024

See all related articles

Search research articles

Related Experiment Video

Updated: May 23, 2026

Single-Particle Cryo-EM Data Collection with Stage Tilt using Leginon

Single-Particle Cryo-EM Data Collection with Stage Tilt using Leginon

Published on: July 1, 2022

Viewing Angle Classification of Cryo-Electron Microscopy Images Using Eigenvectors.

A Singer¹, Z Zhao, Y Shkolnisky

¹Department of Mathematics and PACM, Princeton University, Fine Hall, Washington Road, Princeton, NJ 08544-1000 ( amits@math.princeton.edu ).

SIAM Journal on Imaging Sciences

|April 17, 2012

Summary

This summary is machine-generated.

This study presents a robust and efficient algorithm for identifying noisy cryo-electron microscopy (cryo-EM) images. This crucial step enhances 3D macromolecular structure determination by improving class averages.

More Related Videos

Single Particle Cryo-Electron Microscopy: From Sample to Structure

Single Particle Cryo-Electron Microscopy: From Sample to Structure

Published on: May 29, 2021

Related Experiment Videos

Last Updated: May 23, 2026

Single-Particle Cryo-EM Data Collection with Stage Tilt using Leginon

Single-Particle Cryo-EM Data Collection with Stage Tilt using Leginon

Published on: July 1, 2022

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:

Cryo-electron microscopy (cryo-EM) is vital for determining macromolecular structures.
Accurate 3D reconstruction relies on identifying and aligning 2D projection images.
Noise and unknown viewing angles present significant challenges in cryo-EM data processing.

Purpose of the Study:

To develop a novel algorithm for identifying noisy cryo-EM images with similar viewing angles.
To improve the initial steps of 3D structure determination in cryo-EM.
To enhance the quality of class averages through improved image selection.

Main Methods:

The algorithm identifies noisy cryo-EM images of nearby viewing angles.
It utilizes the computation of top eigenvectors of a sparse Hermitian matrix.
The method is designed for efficiency in terms of runtime and memory.

Main Results:

The algorithm demonstrates extreme robustness to noise in cryo-EM images.
Numerical experiments confirm the algorithm's effectiveness and efficiency.
Identified images can be rotationally aligned and averaged for better quality class averages.

Conclusions:

The developed algorithm is a significant advancement for cryo-EM data processing.
Its robustness and efficiency facilitate more accurate 3D structure determination.
This method provides a reliable foundation for subsequent cryo-EM analysis steps.