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Related Concept Videos

Flow Cytometry01:23

Flow Cytometry

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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: Apr 17, 2026

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations
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Expression profiling. Combinatorial labeling of single cells for gene expression cytometry.

H Christina Fan1, Glenn K Fu1, Stephen P A Fodor2

  • 1Cellular Research, Inc., 3183 Porter Drive, Palo Alto, CA 94304, USA.

Science (New York, N.Y.)
|February 7, 2015
PubMed
Summary

This study introduces a simple gene expression cytometry method using next-generation sequencing and stochastic barcoding. The technique enables digital gene expression profiling of thousands of single cells, revealing insights into the human hematopoietic system.

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A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations
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Area of Science:

  • Single-cell biology
  • Molecular biology
  • Genomics

Background:

  • Gene expression analysis is crucial for understanding cellular function and heterogeneity.
  • Current methods for single-cell gene expression profiling can be complex and require specialized equipment.

Purpose of the Study:

  • To develop a technically simple yet powerful method for single-cell gene expression cytometry.
  • To enable high-throughput digital gene expression profiling of thousands of cells simultaneously.

Main Methods:

  • Combining next-generation sequencing with stochastic barcoding of single cells.
  • Utilizing a combinatorial library of beads with cell- and molecular-barcoding capture probes.
  • Reconstructing digital gene expression profiles without robotics or automation.

Main Results:

  • Successfully applied the technology to dissect the human hematopoietic system.
  • Characterized heterogeneous responses to in vitro stimulation.
  • Demonstrated high sensitivity for detecting low-abundance transcripts and rare cells.

Conclusions:

  • The developed gene expression cytometry approach is technically simple and scalable.
  • Enables high-throughput analysis of thousands to hundreds of thousands of cells.
  • Provides valuable insights into complex biological systems like hematopoiesis.