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Flow Cytometry

Flow Cytometry

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.
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Related Experiment Video

Updated: Jun 17, 2026

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

Published on: January 16, 2019

A software framework enabling analysis of plate-based flow cytometry data for high-throughput screening.

Rick A Stanton¹, Sonia Escobar, Gary S Elliott

¹Chemistry Research and Discovery, Amgen Inc., Thousand Oaks, California 91320, USA. rstanton@amgen.com

Assay and Drug Development Technologies

|December 29, 2009

Summary

This summary is machine-generated.

This study introduces a novel software framework for analyzing high-throughput flow cytometry (FCM) data. The automated analysis significantly reduces time for gating and data interpretation in FCM experiments.

More Related Videos

Analyzing Platelet Subpopulations by Multi-color Flow Cytometry

Analyzing Platelet Subpopulations by Multi-color Flow Cytometry

Published on: June 10, 2025

Related Experiment Videos

Last Updated: Jun 17, 2026

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

Published on: January 16, 2019

Analyzing Platelet Subpopulations by Multi-color Flow Cytometry

Analyzing Platelet Subpopulations by Multi-color Flow Cytometry

Published on: June 10, 2025

Area of Science:

Biotechnology
Cell Biology
Computational Biology

Background:

Flow cytometry (FCM) is crucial for cell analysis in research and diagnostics.
High-throughput screening (HTS) generates vast amounts of FCM data.
Manual data analysis in FCM is time-consuming and requires significant intervention.

Purpose of the Study:

To develop a novel, algorithmically flexible software framework for analyzing plate-based FCM data.
To automate the gating, data reduction, and interpretation processes for HTS FCM experiments.
To enable rapid visual assessment of experimental results.

Main Methods:

Development of an internally created software framework for FCM data analysis.
Implementation of a post-treatment pooling strategy for data processing.
Automated gating, percent of control (POC) calculation, and data assembly for >87,000 wells.

Main Results:

>87,000 individual wells were automatically gated and analyzed.
Over 240,000 compounds were assessed using the novel framework.
Researchers could visually assess wells of interest within minutes, drastically reducing analysis time.

Conclusions:

The developed software framework significantly streamlines high-throughput flow cytometry data analysis.
Automated processing enables faster and more efficient interpretation of large FCM datasets.
This tool accelerates discovery in research and diagnostics utilizing FCM HTS.