flow cytometry
Definition
Flow cytometry is a high-throughput analytical technique that simultaneously measures multiple physical and chemical characteristics of individual cells or particles as they flow in a fluid stream through a laser beam. The technology detects fluorescent signals from labeled antibodies or dyes bound to cellular components, enabling quantification of cell surface markers, intracellular proteins, DNA content, and cell viability. Flow cytometry can analyze thousands of cells per second, providing statistical data on cell populations and identifying rare subpopulations. It is essential for immunophenotyping, cell cycle analysis, apoptosis detection, and functional assays. Modern instruments can measure 20+ parameters simultaneously, making it indispensable for immunology, cancer research, stem cell biology, and clinical diagnostics.
Visualize flow cytometry in Nodes Bio
Researchers can use Nodes Bio to map relationships between flow cytometry markers and cellular phenotypes as network graphs. Visualize how multiple surface markers define immune cell subsets, connect marker expression patterns to signaling pathways, or model the hierarchical relationships in cell differentiation. Network analysis reveals co-expression patterns and identifies key markers that distinguish cell populations, supporting gating strategy optimization and biomarker discovery.
Visualization Ideas:
- Marker co-expression networks showing which cell surface proteins are expressed together on specific immune cell subsets
- Hierarchical cell differentiation networks mapping how marker expression changes define developmental stages from stem cells to mature populations
- Multi-parameter gating strategy networks illustrating sequential marker-based cell population identification and their relationships
Example Use Case
An immunologist studying T cell exhaustion in cancer uses flow cytometry to measure 15 surface markers (PD-1, TIM-3, LAG-3, CD8, CD4, etc.) on tumor-infiltrating lymphocytes. The complex multi-parameter data reveals several distinct exhausted T cell subpopulations with varying functional capacities. By mapping marker co-expression patterns and their connections to cytokine production and cytotoxicity assays in a network, the researcher identifies a specific marker combination associated with therapeutic response to checkpoint inhibitors, potentially predicting patient outcomes.