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

Flow Cytometry01:23

Flow Cytometry

13.2K
The development of flow cytometry techniques began in 1934 with initial attempts by Andrew Moldavan, a bacteriologist who counted the cells in a flowing capillary system. Moldavan pumped cells through a capillary tube focused under a microscope for visualization. The invention of photometry allowed the measurement of differentially-stained cells, and Louis Kamentsky developed the first multiparameter flow cytometer in 1965 to identify and count the cancer cells in cervical tissue specimens.
In...
13.2K

You might also read

Related Articles

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

Sort by
Same author

A phase 1 clinical trial of a multi-antigen SARS-CoV DNA vaccine as a booster after dose three spike-based mRNA vaccinations.

Molecular therapy. Advances·2026
Same author

Intestinal resident effector-memory CD4 T cells on the adaptive-innate spectrum comprise IL-18 reactivity and adaptive CMV specificity.

Science advances·2026
Same author

Three-year follow-up of the COVAXID trial: real-world assessment of SARS-CoV-2 mRNA vaccine immunogenicity in immunocompromised individuals highlights increasing roles of hybrid and passive immunity.

EBioMedicine·2026
Same author

Translational bioinformatics stalls at implementation.

Briefings in bioinformatics·2026
Same author

HIV-1 viral load and reservoir size remain stable following SARS-CoV-2 mRNA vaccination in people with HIV.

HIV medicine·2026
Same author

Memory T cell aging and rejuvenation.

Immunity·2026
Same journal

The 1st Mediterranean Meeting on Flow Cytometry: Forging New Collaborations Across the Mediterranean and Beyond.

Cytometry. Part A : the journal of the International Society for Analytical Cytology·2026
Same journal

Publication Guidelines for Optimized Multiparameter Immunolabeling Panels (OMIPs).

Cytometry. Part A : the journal of the International Society for Analytical Cytology·2026
Same journal

A Modular High-Parameter Flow Cytometry Framework: Pre-Analytical Optimization and Validation for Clinical Research.

Cytometry. Part A : the journal of the International Society for Analytical Cytology·2026
Same journal

Quantitative Detection of Entotic Cell-In-Cell Structures Using Deformable Segmentation and Deep Learning.

Cytometry. Part A : the journal of the International Society for Analytical Cytology·2026
Same journal

Comparison of Tissue Preparations to Identify and Phenotype T Cells in Human Colorectal Tumor Tissue.

Cytometry. Part A : the journal of the International Society for Analytical Cytology·2026
Same journal

Refractive Index-Correlated Pseudocoloring for Adaptive Color Fusion in Holotomographic Cytology.

Cytometry. Part A : the journal of the International Society for Analytical Cytology·2026
See all related articles

Related Experiment Video

Updated: Apr 26, 2026

Far-Red Fluorescent Senescence-Associated β-Galactosidase Probe for Identification and Enrichment of Senescent Tumor Cells by Flow Cytometry
14:01

Far-Red Fluorescent Senescence-Associated β-Galactosidase Probe for Identification and Enrichment of Senescent Tumor Cells by Flow Cytometry

Published on: September 13, 2022

5.3K

NetFCM: a semi-automated web-based method for flow cytometry data analysis.

Juliet Frederiksen1, Marcus Buggert, Annika C Karlsson

  • 1Center for Biological Sequence Analysis, Technical University of Denmark, Building 208, DK-2800, Kongens Lyngby, Denmark.

Cytometry. Part a : the Journal of the International Society for Analytical Cytology
|July 22, 2014
PubMed
Summary
This summary is machine-generated.

NetFCM is a new semi-automatic tool that simplifies complex flow cytometry (FCM) data analysis for immune cell identification. It accurately mimics manual gating, reducing subjectivity and analysis time for T cell responses.

Keywords:
cellular+data analysisflow cytometryimmunitysemi-automatedweb-based

More Related Videos

Techniques for the Analysis of Extracellular Vesicles Using Flow Cytometry
09:39

Techniques for the Analysis of Extracellular Vesicles Using Flow Cytometry

Published on: March 17, 2015

22.9K
Analysis of Cell Suspensions Isolated from Solid Tissues by Spectral Flow Cytometry
11:08

Analysis of Cell Suspensions Isolated from Solid Tissues by Spectral Flow Cytometry

Published on: May 5, 2017

12.3K

Related Experiment Videos

Last Updated: Apr 26, 2026

Far-Red Fluorescent Senescence-Associated β-Galactosidase Probe for Identification and Enrichment of Senescent Tumor Cells by Flow Cytometry
14:01

Far-Red Fluorescent Senescence-Associated β-Galactosidase Probe for Identification and Enrichment of Senescent Tumor Cells by Flow Cytometry

Published on: September 13, 2022

5.3K
Techniques for the Analysis of Extracellular Vesicles Using Flow Cytometry
09:39

Techniques for the Analysis of Extracellular Vesicles Using Flow Cytometry

Published on: March 17, 2015

22.9K
Analysis of Cell Suspensions Isolated from Solid Tissues by Spectral Flow Cytometry
11:08

Analysis of Cell Suspensions Isolated from Solid Tissues by Spectral Flow Cytometry

Published on: May 5, 2017

12.3K

Area of Science:

  • Immunology
  • Computational Biology
  • Bioinformatics

Background:

  • Multi-parametric flow cytometry (FCM) is crucial for single-cell immune system analysis.
  • Increasingly complex FCM data requires advanced analytical methods.
  • Manual gating is time-consuming and subjective.

Purpose of the Study:

  • To develop NetFCM, a semi-automatic gating strategy for FCM data analysis.
  • To enable efficient subset identification and quantification of differences between samples.
  • To classify and cluster samples using multidimensional FCM data.

Main Methods:

  • NetFCM employs clustering and principal component analysis (PCA).
  • It integrates statistical methods to replicate manual gating.
  • The tool was validated on peripheral blood mononuclear cells from HIV-infected individuals.

Main Results:

  • NetFCM successfully clustered virus-specific CD8+ T cells based on cytokine responses (IFNγ, TNF).
  • The tool identified HIV- and CMV-specific T cell responses.
  • Results correlated well with traditional manual gating strategies.

Conclusions:

  • NetFCM effectively mimics classical FCM data analysis for T cell population identification.
  • The tool reduces subjectivity and time investment in FCM data analysis.
  • NetFCM offers a valuable approach for analyzing complex immune cell data.