Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Super-resolution Fluorescence Microscopy

Super-resolution Fluorescence Microscopy

Super-resolution fluorescence microscopy (SRFM) provides a better resolution than conventional fluorescence microscopy by reducing the point spread function (PSF). PSF is the light intensity distribution from a point that causes it to appear blurred. Due to PSF, each fluorescing point appears bigger than its actual size, and it is the PSF interference of nearby fluorophores that causes the blurred image. Various approaches to achieving higher resolution through SRFM have recently been...

Electron Microscope Tomography and Single-particle Reconstruction

Electron Microscope Tomography and Single-particle Reconstruction

Transmission electron microscopy (TEM) can be used to determine the 3D structure of biological samples with the help of techniques such as electron microscope tomography and single-particle reconstruction. While single-particle reconstruction can examine macromolecules and macromolecular complexes in vitro conditions only, tomography permits the study of cell components or small cells in vivo.
Electron Tomography
Electron tomography can be performed either in TEM or STEM (scanning transmission...

You might also read

Related Articles

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

Sort by

Same author

LacI strikes a balance between stability and inducibility.

Nucleic acids research·2026

Same author

Reperfusion treatment strategies in acute pulmonary embolism: Study protocol for a multicenter prospective observational study in the Nordic countries (PE-NORDIC).

Thrombosis research·2026

Same author

Metabolic syndrome and venous thromboembolism: the role of abdominal obesity and sex differences.

Journal of thrombosis and thrombolysis·2026

Same author

[New classification criteria for antiphospholipid syndrome: implications and clinical significance].

Lakartidningen·2025

Same author

Culture-free detection of bacteria from blood for rapid sepsis diagnosis.

NPJ digital medicine·2025

Same author

Thrombotic risk determined by <i>ABO</i>, <i>F8</i>, and <i>VWF</i> variants in a population-based cohort study.

Research and practice in thrombosis and haemostasis·2025

Same journal

3DICE: Interpretable 3D Cross-Modal Learning for Drug-Target Interaction Prediction and Large-Scale Drug Discovery.

Bioinformatics (Oxford, England)·2026

Same journal

KASSPer: Kinase Active Site Structure Prediction using Protein and Ligand Language Models and Its Application to Virtual Screening.

Bioinformatics (Oxford, England)·2026

Same journal

IDR searcher: a search engine solution for public image resources.

Bioinformatics (Oxford, England)·2026

Same journal

KCFtools: Rapid alignment-free method for introgression screening and GWAS using k-mer profiles.

Bioinformatics (Oxford, England)·2026

Same journal

Meta2DB: Curated shotgun metagenomic feature sets and metadata for health state prediction.

Bioinformatics (Oxford, England)·2026

Same journal

conMItion: an R package adjusting confounding factors for associations in multi-omics.

Bioinformatics (Oxford, England)·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Mar 21, 2026

Open-source Single-particle Analysis for Super-resolution Microscopy with VirusMapper

Open-source Single-particle Analysis for Super-resolution Microscopy with VirusMapper

Published on: April 9, 2017

Simulated single molecule microscopy with SMeagol.

Martin Lindén¹, Vladimir Ćurić¹, Alexis Boucharin¹

¹Department of Cell and Molecular Biology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden.

Bioinformatics (Oxford, England)

|May 7, 2016

Summary

This summary is machine-generated.

SMeagol is a new software tool that simulates realistic microscopy data for live cell imaging. This tool aids in developing and validating advanced analysis methods for single-molecule microscopy.

More Related Videos

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

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

Published on: September 5, 2019

Single Molecule Fluorescence Microscopy on Planar Supported Bilayers

Single Molecule Fluorescence Microscopy on Planar Supported Bilayers

Published on: October 31, 2015

Related Experiment Videos

Last Updated: Mar 21, 2026

Open-source Single-particle Analysis for Super-resolution Microscopy with VirusMapper

Open-source Single-particle Analysis for Super-resolution Microscopy with VirusMapper

Published on: April 9, 2017

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

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

Published on: September 5, 2019

Single Molecule Fluorescence Microscopy on Planar Supported Bilayers

Single Molecule Fluorescence Microscopy on Planar Supported Bilayers

Published on: October 31, 2015

Area of Science:

Computational Biology
Biophysics
Microscopy

Background:

Live cell single-molecule microscopy generates complex data.
Advanced analysis methods are crucial for extracting biological insights.
Development and validation of these methods require realistic simulation data.

Purpose of the Study:

To introduce SMeagol, a software tool for simulating realistic microscopy data.
To support the development, validation, and optimization of analysis methods for live cell microscopy.

Main Methods:

SMeagol utilizes spatial systems biology models for data simulation.
It employs reaction-diffusion simulations using compiled C binaries.
The software is compatible with Matlab R2014 and later versions.

Main Results:

SMeagol generates highly realistic microscopy data.
The simulated data facilitates the testing of advanced analysis techniques.
The tool is designed for live cell single-molecule microscopy applications.

Conclusions:

SMeagol provides a valuable resource for researchers in live cell microscopy.
It enables robust development and validation of novel data analysis methods.
The software enhances the study of molecular dynamics in living cells.