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 17, 2025

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.4K

Maximum-likelihood model fitting for quantitative analysis of SMLM data.

Yu-Le Wu1,2, Philipp Hoess1, Aline Tschanz1,2

  • 1Cell Biology and Biophysics Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany.

Nature Methods
|December 15, 2022
PubMed
Summary

Related Concept Videos

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

95
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
95
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

75
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
75
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

642
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
642
Calibration Curves: Linear Least Squares01:20

Calibration Curves: Linear Least Squares

1.5K
A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
For data that follow a straight line, the standard method for fitting is the linear...
1.5K
Expected Frequencies in Goodness-of-Fit Tests01:19

Expected Frequencies in Goodness-of-Fit Tests

2.6K
A goodness-of-fit test is conducted to determine whether the observed frequency values are statistically similar to the frequencies expected for the dataset. Suppose the expected frequencies for a dataset are equal such as when predicting the frequency of any number appearing when casting a die. In that case, the expected frequency is the ratio of the total number of observations (n)  to the number of categories (k).
2.6K
Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches01:14

Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches

203
Drug disposition in the body is a complex process and can be studied using two major approaches: the model and the model-independent approaches.
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
203

You might also read

Related Articles

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

Sort by
Same author

VMAT2 dysfunction impairs vesicular dopamine uptake, driving its oxidation and α-synuclein pathology in DJ-1-linked Parkinson's neurons.

Science advances·2026
Same author

Evaluating MINFLUX experimental performance in silico.

Nature communications·2025
Same author

Multi-step implementation of meiotic crossover patterning.

bioRxiv : the preprint server for biology·2025
Same author

In-depth single molecule localization microscopy using adaptive optics and single objective light-sheet microscopy.

Nature communications·2025
Same author

Simple and robust 3D MINFLUX excitation with a variable phase plate.

Light, science & applications·2024
Same author

Universal inverse modeling of point spread functions for SMLM localization and microscope characterization.

Nature methods·2024
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
Same journal

3D pathology-guided microdissection.

Nature methods·2026
See all related articles
This summary is machine-generated.

LocMoFit is a new open-source framework for analyzing single-molecule localization microscopy (SMLM) data. It allows researchers to extract detailed biological insights from complex molecular structures without geometric assumptions.

Area of Science:

  • Biophysics
  • Structural Biology
  • Microscopy

Background:

  • Quantitative data analysis is crucial for single-molecule localization microscopy (SMLM) to derive biological insights from fluorophore coordinates.
  • Existing SMLM analysis methods are limited to simple or identical structures, hindering the study of complex biological systems.

Purpose of the Study:

  • To introduce LocMoFit, an open-source framework designed to fit arbitrary models to localization coordinates from SMLM data.
  • To enable the analysis of complex, heterogeneous, and dynamic biological structures with SMLM.

Main Methods:

  • LocMoFit employs a flexible framework to fit user-defined models to SMLM localization data.
  • The software includes routines for model selection, parameter extraction, and analysis of individual structures.

More Related Videos

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
08:27

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Published on: September 27, 2019

7.0K
A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM
13:54

A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM

Published on: August 18, 2023

4.8K

Related Experiment Videos

Last Updated: Aug 17, 2025

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.4K
Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
08:27

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Published on: September 27, 2019

7.0K
A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM
13:54

A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM

Published on: August 18, 2023

4.8K

Main Results:

  • LocMoFit successfully analyzed complex, heterogeneous, and dynamic structures, including in situ structural biology applications.
  • Demonstrated assembly of multi-protein distribution maps for nuclear pore components and calculation of geometry-independent single-particle averages.
  • Enabled time-resolved reconstruction of dynamic processes like endocytosis from static SMLM snapshots.

Conclusions:

  • LocMoFit significantly enhances the information obtainable from SMLM data by providing a versatile tool for quantitative analysis.
  • The framework supports the study of complex biological systems and dynamic processes, advancing in situ structural biology.
  • Extensive simulations, visualizations, and tutorials ensure the robustness and usability of LocMoFit for the scientific community.