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

Cluster Sampling Method01:20

Cluster Sampling Method

12.6K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
12.6K
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

121
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
121

You might also read

Related Articles

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

Sort by
Same author

A physics-informed alternative to Richardson-Lucy deconvolution across SNR regimes without iteration cutoffs.

Nature communications·2026
Same author

Mitochondria directly interact with the nuclear pore complex.

Nature·2026
Same author

Stochastic colonization and host-to-host transmission shape gut bacterial variability.

bioRxiv : the preprint server for biology·2026
Same author

Resolving fluorescently labeled species using highly multiplexed spectral FLIM.

Scientific reports·2026
Same author

Simulation-based inference captures non-Markovian effects as exemplified in protein production kinetics through cell division.

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

Substrate-interacting pore loops of two ATPase subunits determine the degradation efficiency of the 26S proteasome.

Nature communications·2026
Same journal

Gaining biological insights through supervised data visualization.

Nature computational science·2026
Same journal

The inequalities of GPU access.

Nature computational science·2026
Same journal

Social technologies need societal alignment.

Nature computational science·2026
Same journal

The Quantum Optimization Benchmarking Library.

Nature computational science·2026
Same journal

Setting benchmarks for practical quantum utility of combinatorial optimization.

Nature computational science·2026
Same journal

Evidence of scaling advantage on an NP-complete problem with enhanced quantum solvers.

Nature computational science·2026
See all related articles

Related Experiment Video

Updated: Sep 3, 2025

Image Processing Protocol for the Analysis of the Diffusion and Cluster Size of Membrane Receptors by Fluorescence Microscopy
12:15

Image Processing Protocol for the Analysis of the Diffusion and Cluster Size of Membrane Receptors by Fluorescence Microscopy

Published on: April 9, 2019

8.8K

Diffraction-Limited Molecular Cluster Quantification with Bayesian Nonparametrics.

J Shepard Bryan1, Ioannis Sgouralis2, Steve Pressé1,3

  • 1Center for Biological Physics, Arizona State University.

Nature Computational Science
|July 25, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a novel Bayesian method to count fluorophores and track their photophysical states simultaneously. This approach enhances the analysis of molecular clusters in cells, providing kinetic insights.

Keywords:
Bayesian nonparametricsbiophysicsdata analysismolecular biologyphotobleachingstochastic dynamicssuperresolution

More Related Videos

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
12:11

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Published on: April 8, 2020

8.3K
Confocal Microscopy Reveals Cell Surface Receptor Aggregation Through Image Correlation Spectroscopy
06:51

Confocal Microscopy Reveals Cell Surface Receptor Aggregation Through Image Correlation Spectroscopy

Published on: August 2, 2018

7.2K

Related Experiment Videos

Last Updated: Sep 3, 2025

Image Processing Protocol for the Analysis of the Diffusion and Cluster Size of Membrane Receptors by Fluorescence Microscopy
12:15

Image Processing Protocol for the Analysis of the Diffusion and Cluster Size of Membrane Receptors by Fluorescence Microscopy

Published on: April 9, 2019

8.8K
Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
12:11

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Published on: April 8, 2020

8.3K
Confocal Microscopy Reveals Cell Surface Receptor Aggregation Through Image Correlation Spectroscopy
06:51

Confocal Microscopy Reveals Cell Surface Receptor Aggregation Through Image Correlation Spectroscopy

Published on: August 2, 2018

7.2K

Area of Science:

  • Cellular and Molecular Biology
  • Biophysics
  • Computational Biology

Background:

  • Cellular processes rely on molecular interactions within confined spaces.
  • Existing methods for counting fluorophores (e.g., photobleaching) do not capture photophysical dynamics or kinetic rates.
  • Analyzing molecular clusters requires understanding both composition and kinetics.

Purpose of the Study:

  • To develop a method for simultaneous fluorophore enumeration and photophysical state trajectory determination.
  • To provide a versatile framework for interpreting complex time-resolved fluorescence data from molecular assemblies.
  • To enable the study of molecular cluster dynamics and kinetics.

Main Methods:

  • Utilized Bayesian nonparametrics for estimating unknown numbers of active molecules.
  • Employed specialized Monte Carlo algorithms for deriving fluorophore state estimates.
  • Developed a framework applicable to both initially fluorescent and photoactivated fluorophores.

Main Results:

  • Successfully enumerated fluorophores and determined individual photophysical state trajectories.
  • Benchmarked the formulation on both synthetic and real experimental data.
  • Demonstrated the framework's capability to analyze complex time traces from up to 100 simultaneous fluorophores.

Conclusions:

  • The proposed method offers a comprehensive approach to quantifying fluorophores and their dynamic behavior.
  • This framework advances the study of molecular cluster composition and kinetics within diffraction-limited cellular regions.
  • The method is adaptable for various photophysical dynamics and fluorophore activation schemes.