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

Computed Tomography01:10

Computed Tomography

9.1K
Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
9.1K
Electron Microscope Tomography and Single-particle Reconstruction01:07

Electron Microscope Tomography and Single-particle Reconstruction

3.0K
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...
3.0K
Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

492
DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...
492

You might also read

Related Articles

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

Sort by
Same author

Tomogram exploration through template matching and deep learning.

Current opinion in structural biology·2026
Same author

Cargo-Adaptor Cooperation Programs Retromer Coat Architecture.

bioRxiv : the preprint server for biology·2026
Same author

Continuum architecture dynamics of vesicle tethering in exocytosis.

Cell·2026
Same author

Geometry-aware template matching for cryo-electron tomograms in Dynamo.

Structure (London, England : 1993)·2025
Same author

Few-shot learning for non-vitrified ice segmentation.

Scientific reports·2025
Same author

Automated fiducial-based alignment of cryo-electron tomography tilt series in Dynamo.

Structure (London, England : 1993)·2024

Related Experiment Video

Updated: Mar 1, 2026

Using Tomoauto: A Protocol for High-throughput Automated Cryo-electron Tomography
11:33

Using Tomoauto: A Protocol for High-throughput Automated Cryo-electron Tomography

Published on: January 30, 2016

11.5K

The Dynamo package for tomography and subtomogram averaging: components for MATLAB, GPU computing and EC2 Amazon Web

Daniel Castaño-Díez1

  • 1BioEM Lab at C-CINA, Biozentrum, University of Basel, Matenstrasse 26, CH-4058 Basel, Switzerland.

Acta Crystallographica. Section D, Structural Biology
|June 6, 2017
PubMed
Summary
This summary is machine-generated.

Dynamo is a powerful package for tomographic data processing, offering advanced subtomogram averaging, alignment, and classification. It optimizes performance through multicore parallelization and GPU acceleration, enhancing scientific discovery.

Keywords:
Amazon EC2GPU computingcloud computingcryo-electron tomographysubtomogram averaging

More Related Videos

Using Synchrotron Radiation Microtomography to Investigate Multi-scale Three-dimensional Microelectronic Packages
08:46

Using Synchrotron Radiation Microtomography to Investigate Multi-scale Three-dimensional Microelectronic Packages

Published on: April 13, 2016

10.5K
Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging
08:55

Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging

Published on: July 12, 2022

6.0K

Related Experiment Videos

Last Updated: Mar 1, 2026

Using Tomoauto: A Protocol for High-throughput Automated Cryo-electron Tomography
11:33

Using Tomoauto: A Protocol for High-throughput Automated Cryo-electron Tomography

Published on: January 30, 2016

11.5K
Using Synchrotron Radiation Microtomography to Investigate Multi-scale Three-dimensional Microelectronic Packages
08:46

Using Synchrotron Radiation Microtomography to Investigate Multi-scale Three-dimensional Microelectronic Packages

Published on: April 13, 2016

10.5K
Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging
08:55

Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging

Published on: July 12, 2022

6.0K

Area of Science:

  • Cryo-electron microscopy data processing
  • Computational structural biology
  • Image analysis software

Background:

  • Subtomogram averaging requires efficient tools for processing large tomographic datasets.
  • Existing software may lack comprehensive features for data management, visualization, and performance optimization.

Purpose of the Study:

  • To present a technical description of the Dynamo package for tomographic data processing.
  • To highlight Dynamo's strategies for optimizing computing performance in subtomogram averaging.

Main Methods:

  • Dynamo utilizes a hybrid MATLAB and C++ architecture for efficient computation.
  • It incorporates multicore parallelization and supports GPU acceleration for intensive tasks.
  • Cloud-based access via Amazon EC2 is provided for scalable computing.

Main Results:

  • Dynamo offers advanced alignment and classification strategies for subtomogram averaging.
  • Its data management module facilitates organization and visualization of tomographic experiments.
  • Significant speedups are achieved through parallelization and GPU utilization.

Conclusions:

  • Dynamo provides a robust and efficient solution for subtomogram averaging and tomographic data analysis.
  • Its performance optimization strategies and flexible architecture benefit researchers in structural biology.
  • Accessible cloud computing options lower the barrier to entry for advanced data processing.