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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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Updated: Jul 2, 2026

Imaging Flow Cytometry to Study Microbial Autoaggregation

Imaging Flow Cytometry to Study Microbial Autoaggregation

Published on: September 29, 2023

Gating-ML: XML-based gating descriptions in flow cytometry.

Josef Spidlen¹, Robert C Leif, Wayne Moore

¹Terry Fox Laboratory, BC Cancer Agency, Vancouver, British Columbia, Canada.

Cytometry. Part a : the Journal of the International Society for Analytical Cytology

|September 6, 2008

Summary

This summary is machine-generated.

A new standard, Gating-ML, addresses software interoperability for flow cytometry (FCM) data analysis. This XML-based mechanism enables standardized data exchange, improving reproducibility and enabling advanced analyses.

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Area of Science:

Biomedical data analysis
Computational biology
Cytometry

Background:

Software interoperability is a major challenge in flow cytometry (FCM) data analysis.
Lack of standardized data exchange hinders reproducibility and the use of diverse analytical tools.

Purpose of the Study:

To develop a standardized mechanism for describing and exchanging flow cytometry gating information.
To enhance interoperability among FCM data analysis software.

Main Methods:

Development of Gating-ML, an XML-based open specification.
Formal description of gates, data transformations, and compensation within Gating-ML.
Adoption of Gating-ML as a Candidate Recommendation by the ISAC Data Standards Task Force (DSTF).

Main Results:

Gating-ML provides a standardized method for encoding gating strategies.
The standard facilitates the exchange of gating descriptions, similar to how FCS facilitates raw data exchange.
The ISAC DSTF confirms that Gating-ML meets the requirements for a gating exchange standard.

Conclusions:

Gating-ML is poised to significantly improve reproducibility in FCM data analysis.
The standard will foster new collaborative opportunities and enable advanced analytical methods.
Adoption of Gating-ML will overcome previous bottlenecks in FCM data analysis.