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

2.9K
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...
2.9K

You might also read

Related Articles

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

Sort by
Same author

Unsupervised Machine Learning-Based Process Analytical Tools for Near Real-Time Cell Morphology Analysis During CAR-T Cell Manufacturing.

Biotechnology and bioengineering·2025
Same author

Representative training data sets are critical for accurate machine-learning classification of microscopy images of particles formed by lipase-catalyzed polysorbate hydrolysis.

Journal of pharmaceutical sciences·2025
Same author

Stain-Free Approach to Determine and Monitor Cell Heath Using Supervised and Unsupervised Image-Based Deep Learning.

Journal of pharmaceutical sciences·2024
Same author

Features in Backgrounds of Microscopy Images Introduce Biases in Machine Learning Analyses.

Journal of pharmaceutical sciences·2024
Same author

Supervised and unsupervised machine learning approaches for monitoring subvisible particles within an aluminum-salt adjuvanted vaccine formulation.

Biotechnology and bioengineering·2024
Same author

Motion of VAPB molecules reveals ER-mitochondria contact site subdomains.

Nature·2024

Related Experiment Video

Updated: Apr 20, 2026

An In Vitro Single-Molecule Imaging Assay for the Analysis of Cap-Dependent Translation Kinetics
09:52

An In Vitro Single-Molecule Imaging Assay for the Analysis of Cap-Dependent Translation Kinetics

Published on: September 15, 2020

3.6K

Data-driven techniques for detecting dynamical state changes in noisily measured 3D single-molecule trajectories.

Christopher P Calderon1

  • 1Ursa Analytics, Denver, CO 80212, USA. chris.calderon@ursaanalytics.com.

Molecules (Basel, Switzerland)
|November 15, 2014
PubMed
Summary

This study introduces a new data-driven method, Hierarchical Dirichlet Process Switching Linear Dynamical System (HDP-SLDS), for analyzing complex single-molecule data. It accurately detects molecular state changes in live cells, overcoming experimental noise and environmental challenges.

More Related Videos

Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules
10:20

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

Published on: September 5, 2019

9.0K
High-Speed Magnetic Tweezers for Nanomechanical Measurements on Force-Sensitive Elements
08:50

High-Speed Magnetic Tweezers for Nanomechanical Measurements on Force-Sensitive Elements

Published on: May 12, 2023

3.0K

Related Experiment Videos

Last Updated: Apr 20, 2026

An In Vitro Single-Molecule Imaging Assay for the Analysis of Cap-Dependent Translation Kinetics
09:52

An In Vitro Single-Molecule Imaging Assay for the Analysis of Cap-Dependent Translation Kinetics

Published on: September 15, 2020

3.6K
Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules
10:20

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

Published on: September 5, 2019

9.0K
High-Speed Magnetic Tweezers for Nanomechanical Measurements on Force-Sensitive Elements
08:50

High-Speed Magnetic Tweezers for Nanomechanical Measurements on Force-Sensitive Elements

Published on: May 12, 2023

3.0K

Area of Science:

  • Biophysics
  • Computational Biology
  • Statistical Physics

Background:

  • Live-cell molecular interactions are studied using optical microscopy and nanoscale probes.
  • Analyzing in vivo single-molecule data is challenging due to complex cellular environments and experimental noise.
  • Existing methods struggle with time-varying forces and require pre-defined numbers of hidden states.

Purpose of the Study:

  • To demonstrate the application of the Hierarchical Dirichlet Process Switching Linear Dynamical System (HDP-SLDS) for analyzing single-molecule experimental data.
  • To address challenges in live-cell molecular dynamics analysis, including noise and complex environments.
  • To provide a data-driven method for detecting molecular state changes without a priori assumptions about hidden states.

Main Methods:

  • Utilized the Hierarchical Dirichlet Process Switching Linear Dynamical System (HDP-SLDS) framework.
  • Applied the method to time-series data simulating single-molecule experiments, including single particle tracking (SPT).
  • Compared HDP-SLDS performance against state-of-the-art Hidden Markov Modeling techniques using large-scale simulations.

Main Results:

  • HDP-SLDS effectively detects subtle and abrupt state changes in noisy time-series data.
  • The approach successfully accounts for temporal dependencies from random and systematic forces.
  • The number of hidden states is inferred automatically, eliminating the need for subjective selection.

Conclusions:

  • HDP-SLDS offers a robust, data-driven approach for analyzing complex single-molecule dynamics in live cells.
  • This method overcomes limitations of traditional techniques by adaptively determining system states and change points.
  • The findings have significant implications for advancing our understanding of molecular interactions in biological systems.