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 Experiment Video

Updated: Aug 23, 2025

Proteome-wide Quantification of Labeling Homogeneity at the Single Molecule Level
08:29

Proteome-wide Quantification of Labeling Homogeneity at the Single Molecule Level

Published on: April 19, 2019

6.2K

Don't Be Fooled by Randomness: Valid p-Values for Single Molecule Microscopy.

Magdalena C Schneider1, Gerhard J Schütz1

  • 1Institute of Applied Physics, TU Wien, Vienna, Austria.

Frontiers in Bioinformatics
|October 28, 2022
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Chromatix: a differentiable, GPU-accelerated wave-optics library.

Nature methods·2026
Same author

Chromatix: a differentiable, GPU-accelerated wave-optics library.

bioRxiv : the preprint server for biology·2026
Same author

Quantitative Mapping of the Lipid Nanoenvironment around Transmembrane Proteins in Living Cells.

ACS nano·2026
Same author

Refractive Index Mapping below the Diffraction Limit via Single Molecule Localization Microscopy.

ACS nano·2025
Same author

Single-molecule FRET and tracking of transfected biomolecules in living cells.

Biophysical journal·2025
Same author

Cell membrane cholesterol affects serotonin transporter efflux due to altered transporter oligomerization.

Molecular psychiatry·2025

Statistical significance testing, using p-values, helps researchers distinguish true effects from random chance in data. This study introduces valid methods for applying significance testing to single-molecule microscopy data, including nanoclustering and trajectory analysis.

Area of Science:

  • Quantitative biology
  • Statistical analysis
  • Biophysics

Background:

  • Human pattern recognition can overestimate significance in random data.
  • Statistical significance testing with p-values is crucial for hypothesis validation.
  • Significance testing is underutilized in biophysics and single-molecule studies.

Purpose of the Study:

  • To propose significance testing as a valuable tool for quantitative single-molecule biology.
  • To describe methods for obtaining valid p-values in specific single-molecule microscopy applications.
  • To address limitations in current statistical approaches for complex biological data.

Main Methods:

  • Extension of the 2-CLASTA method for nanoclustering analysis to yield pooled p-values.
  • Development of a block permutation test for analyzing correlated single-molecule trajectory data.
Keywords:
FRETnanoclusteringsingle molecule localization microscopysingle molecule microscopystatistical significance testing

More Related Videos

Counting Proteins in Single Cells with Addressable Droplet Microarrays
12:25

Counting Proteins in Single Cells with Addressable Droplet Microarrays

Published on: July 6, 2018

8.6K
An Optimized Single-Molecule Pull-Down Assay for Quantification of Protein Phosphorylation
07:45

An Optimized Single-Molecule Pull-Down Assay for Quantification of Protein Phosphorylation

Published on: June 6, 2022

3.0K

Related Experiment Videos

Last Updated: Aug 23, 2025

Proteome-wide Quantification of Labeling Homogeneity at the Single Molecule Level
08:29

Proteome-wide Quantification of Labeling Homogeneity at the Single Molecule Level

Published on: April 19, 2019

6.2K
Counting Proteins in Single Cells with Addressable Droplet Microarrays
12:25

Counting Proteins in Single Cells with Addressable Droplet Microarrays

Published on: July 6, 2018

8.6K
An Optimized Single-Molecule Pull-Down Assay for Quantification of Protein Phosphorylation
07:45

An Optimized Single-Molecule Pull-Down Assay for Quantification of Protein Phosphorylation

Published on: June 6, 2022

3.0K
  • Application of methods to single-molecule localization microscopy and FRET trajectories.

    • Main Results:

    • The extended 2-CLASTA method provides a valid overall p-value for pooled nanoclustering data.
    • The block permutation test enables valid statistical assessment of single-molecule trajectories.
    • Demonstrated applicability in analyzing molecular distributions and FRET data.

    Conclusions:

    • Significance testing offers a probabilistic framework to support quantitative judgments in single-molecule biology.
    • The presented methods enhance the statistical rigor for analyzing nanoclustering and trajectory data.
    • Encourages wider adoption of significance testing in biophysics research.