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

Protein Dynamics in Living Cells01:19

Protein Dynamics in Living Cells

2.0K
Different fluorescence-based techniques are used to study the protein dynamics in living cells. These techniques include FRAP, FRET, and PET.
Fluorescent recovery after photobleaching (FRAP) is a fluorescent-protein-based detection technique used to quantify protein movement rates within the cell. This method exposes a small portion of the cell to an intense laser beam. The laser beam causes permanent photobleaching of the fluorophore-tagged proteins in the exposed region. As the bleached...
2.0K
Protein Diffusion in the Membrane01:24

Protein Diffusion in the Membrane

4.3K
Proteins show rotational as well as lateral diffusion across the membrane. The lateral diffusion of proteins was confirmed through the cell fusion experiment where mouse and human cells were fused, resulting in hybrid cells. When the human and mouse cells fused, the specific membrane proteins on human and mouse cells were marked with the red and green-fluorescent markers, respectively. Initially, the red and green fluorescence was located on the respective hemisphere of the cell. As time...
4.3K

You might also read

Related Articles

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

Sort by
Same author

Live-cell imaging of enhancer-promoter dynamics reveals transient contact-driven gene activation.

bioRxiv : the preprint server for biology·2026
Same author

Membrane bridges and nanodomain partitioning govern membrane protein targeting to lipid droplets.

Nature cell biology·2026
Same author

Naked antisense oligonucleotides remain endolysosomally sequestered despite induced membrane damage.

bioRxiv : the preprint server for biology·2026
Same author

A multimodal adaptive optical microscope for in vivo imaging from molecules to organisms.

Nature methods·2026
Same author

How endosomal PIKfyve inhibition prevents viral membrane fusion and entry.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Seeing the Unseen: Super-Resolution Microscopy in Protein Aggregation Research.

Chemical & biomedical imaging·2026
Same journal

ClairS: a deep-learning method for long-read tumor-normal pair somatic small variant calling.

Nature methods·2026
Same journal

RNAbpFlow: base pair-augmented SE(3) flow matching for conditional RNA 3D structure generation.

Nature methods·2026
Same journal

Spatio-DARLIN enables robust and efficient in situ lineage tracing in mice at single-cell resolution.

Nature methods·2026
Same journal

EasyGrid: a versatile platform for automated cryo-EM sample preparation and quality control.

Nature methods·2026
Same journal

Cloud-based microscope enables live neuroimaging for 24 h and beyond with worldwide access.

Nature methods·2026
Same journal

Deep molecular profiling in three dimensions.

Nature methods·2026
See all related articles

Related Experiment Video

Updated: May 15, 2025

A Simple, Robust, and High Throughput Single Molecule Flow Stretching Assay Implementation for Studying Transport of Molecules Along DNA
12:05

A Simple, Robust, and High Throughput Single Molecule Flow Stretching Assay Implementation for Studying Transport of Molecules Along DNA

Published on: October 1, 2017

8.1K

Deep learning-assisted analysis of single-particle tracking for automated correlation between diffusion and function.

Jacob Kæstel-Hansen1,2,3,4, Marilina de Sautu5,6, Anand Saminathan7,8,9

  • 1Department of Chemistry, University of Copenhagen, Copenhagen, Denmark.

Nature Methods
|May 9, 2025
PubMed
Summary
This summary is machine-generated.

DeepSPT, a deep learning tool, analyzes nanoscale diffusion to reveal cellular functions. This automated approach rapidly extracts biological insights from molecular and organelle motion, accelerating research.

More Related Videos

Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules
00:10

Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules

Published on: September 5, 2019

8.1K
High-resolution Spatiotemporal Analysis of Receptor Dynamics by Single-molecule Fluorescence Microscopy
15:13

High-resolution Spatiotemporal Analysis of Receptor Dynamics by Single-molecule Fluorescence Microscopy

Published on: July 25, 2014

11.3K

Related Experiment Videos

Last Updated: May 15, 2025

A Simple, Robust, and High Throughput Single Molecule Flow Stretching Assay Implementation for Studying Transport of Molecules Along DNA
12:05

A Simple, Robust, and High Throughput Single Molecule Flow Stretching Assay Implementation for Studying Transport of Molecules Along DNA

Published on: October 1, 2017

8.1K
Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules
00:10

Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules

Published on: September 5, 2019

8.1K
High-resolution Spatiotemporal Analysis of Receptor Dynamics by Single-molecule Fluorescence Microscopy
15:13

High-resolution Spatiotemporal Analysis of Receptor Dynamics by Single-molecule Fluorescence Microscopy

Published on: July 25, 2014

11.3K

Area of Science:

  • Cellular and Molecular Biology
  • Biophysics
  • Computational Biology

Background:

  • Subcellular diffusion dynamics are crucial for understanding cellular processes and interactions.
  • Current methods for extracting functional information from nanoscale diffusion are often manual, time-consuming, and challenging.
  • Advances in optical microscopy enable high-precision tracking of molecular and organelle diffusion.

Purpose of the Study:

  • To develop an agnostic and automated deep learning framework for interpreting subcellular diffusion.
  • To enable rapid and efficient extraction of functional information from nanoscale object movement.
  • To demonstrate the utility of diffusion analysis for understanding cellular functions.

Main Methods:

  • Introduction of DeepSPT, a deep learning framework integrated into analysis software.
  • Application of DeepSPT for interpreting two- or three-dimensional temporal diffusion behavior of objects.
  • Utilizing DeepSPT for automated mapping of early viral infection events.

Main Results:

  • DeepSPT achieved high F1 scores in identifying endosomal organelles (81%), clathrin-coated pits (82%), and vesicles (95%).
  • The framework provides rapid analysis, reducing processing time from weeks to seconds.
  • Demonstrated successful automated mapping of early viral infection events.

Conclusions:

  • DeepSPT effectively extracts biological information solely from diffusion patterns.
  • Molecular and subcellular motion, in addition to structure, encodes critical functional information.
  • This deep learning approach offers a powerful tool for advancing cell biology research.