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Related Experiment Video

Updated: Jun 14, 2026

Automated Quantification of Hematopoietic Cell – Stromal Cell Interactions in Histological Images of Undecalcified Bone

Automated Quantification of Hematopoietic Cell – Stromal Cell Interactions in Histological Images of Undecalcified Bone

Published on: April 8, 2015

Ultra-high-scale cytometry-based cellular interaction mapping.

Dominik Vonficht^1,2,3, Lea Jopp-Saile^1,2,3,4,5, Schayan Yousefian^4,5,6

¹Heidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM gGmbH), Heidelberg, Germany.

|August 7, 2025

Summary

This summary is machine-generated.

Interact-omics is a new cytometry framework that maps cellular interactions across all immune cells at high resolution and scale. This method enables detailed study of immunotherapies and infection responses.

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Last Updated: Jun 14, 2026

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Area of Science:

Immunology
Systems Biology
Biomedical Science

Background:

Cellular interactions are crucial for development, tissue homeostasis, and immunity.
Existing single-cell genomic methods for studying cell interactions have limitations in throughput, cost, and cell type specificity.

Purpose of the Study:

To introduce Interact-omics, a cytometry-based framework for mapping cellular landscapes and interactions.
To enable ultra-high resolution and large-scale analysis of all immune cell types and their interactions.

Main Methods:

Development of a cytometry-based framework named Interact-omics.
Application of the framework to analyze cellular interactions in immunotherapy and infection models.

Main Results:

Accurate mapping of cellular landscapes and interactions across all immune cell types at ultra-high resolution and scale.
Demonstration of utility in studying immunotherapy kinetics, mode of action, and personalized response prediction.
Analysis of organism-wide cellular composition and interaction dynamics following in vivo infection.

Conclusions:

Interact-omics offers a scalable solution for mapping cellular interactions.
The framework can be applied to existing or new cytometry datasets.
Broad applications in fundamental biology and applied biomedicine, including immunotherapy and infection research.