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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: Mar 21, 2026

Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software

Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software

Published on: December 16, 2014

A Computational Workflow for Cell Line Profiling by Imaging Mass Cytometry.

Alexandre Bouzekri¹, Amanda Esch¹, Olga Ornatsky¹

¹Standard BioTools Inc, South San Francisco, California, USA.

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

|March 20, 2026

Summary

This summary is machine-generated.

We developed IMC Cell Line Profiler, an open-source computational workflow for analyzing imaging mass cytometry (IMC) data. This tool quantifies cell morphology and phenotypes in tumor cell lines, aiding cancer progression and drug response predictions.

Keywords:

adherent cell lines cisplatin drug treatment computational workflow pipeline high‐dimensional tools imaging mass cytometry morphological phenotypes nuclear state classification protein expression profiling single‐cell imaging segmentation visual rendering analysis

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Last Updated: Mar 21, 2026

Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software

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Isolation and Staining of Mouse Skin Keratinocytes for Cell Cycle Specific Analysis of Cellular Protein Expression by Mass Cytometry

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Published on: May 9, 2019

Area of Science:

Biomedical research
Computational biology
Cancer research

Background:

Single-cell spatial phenotyping using imaging mass cytometry (IMC) is crucial for understanding disease.
Analyzing diverse tumor-derived cancer cell lines is challenging for predicting cancer progression and drug responses.

Purpose of the Study:

To introduce IMC Cell Line Profiler, an adaptable open-source computational workflow.
To enable quantitative segmentation-based analysis and visual rendering of tumor-derived cell lines profiled by IMC.

Main Methods:

Utilized IMC's high resolution and multiplexing capabilities.
Applied custom panels of 20-30 metal-labeled antibodies to profile 10 diverse cell lines.
Developed a computational workflow for analyzing morphology, phenotypic traits, and spatial arrangement.

Main Results:

Generated high-dimensional datasets revealing diverse cellular states with multiple markers.
Applied the computational approach to track morpho-phenotypic changes during cisplatin treatment in a resistant cell line.

Conclusions:

IMC Cell Line Profiler offers versatile open-source tools for IMC data analysis.
This workflow expands the potential of IMC for profiling cell lines and discovering new biological insights.