Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Cell Specific Gene Expression

Cell Specific Gene Expression

Overview of Cell-Matrix Interactions

Overview of Cell-Matrix Interactions

The extracellular matrix or ECM holds cells together to form a tissue and allows the cells within the tissue to communicate. ECM comprises proteins such as fibronectin, collagen, laminin, etc. The most abundant protein in this space is collagen. Collagen fibers are interwoven with carbohydrate-containing protein molecules called proteoglycans. ECM allows cell migration and provides a structural scaffold at cell adhesion that anchors the cell when the extracellular matrix proteins interact with...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

The CARM1 epigenetic enzyme inhibits cross-presenting dendritic cell function in cancer immunity.

Science (New York, N.Y.)·2026

Same author

Optimal gene panel selection for targeted spatial transcriptomics experiments.

Nucleic acids research·2026

Same author

Optimal Gene Panel Selection for Targeted Spatial Transcriptomics Experiments.

bioRxiv : the preprint server for biology·2025

Same author

SpaDiff: Denoising for Sequence-based Spatial Transcriptomics via Diffusion Process.

bioRxiv : the preprint server for biology·2025

Same author

sCCIgen: a high-fidelity spatially resolved transcriptomics data simulator for cell-cell interaction studies.

Genome biology·2025

Same author

Giotto Suite: a multiscale and technology-agnostic spatial multiomics analysis ecosystem.

Nature methods·2025

Search research articles

Related Experiment Video

Updated: Jul 4, 2025

A High-throughput Cell Microarray Platform for Correlative Analysis of Cell Differentiation and Traction Forces

A High-throughput Cell Microarray Platform for Correlative Analysis of Cell Differentiation and Traction Forces

Published on: March 1, 2017

RECCIPE: A new framework assessing localized cell-cell interaction on gene expression in multicellular ST data.

Weiping Ma¹, Xiaoyu Song^2,3, Guo-Cheng Yuan^1,2

¹Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States.

Frontiers in Genetics

|February 8, 2024

Summary

Researchers developed RECCIPE, a new method to analyze cell-cell interactions (CCI) in spatial transcriptomics data. This tool helps understand how cells communicate and impact gene expression, even without single-cell resolution.

Keywords:

Alzheimer disease FDR control cell type proportion cell-cell interaction regression model spatial neighborhood spatial transcriptome

More Related Videos

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

Related Experiment Videos

Last Updated: Jul 4, 2025

A High-throughput Cell Microarray Platform for Correlative Analysis of Cell Differentiation and Traction Forces

A High-throughput Cell Microarray Platform for Correlative Analysis of Cell Differentiation and Traction Forces

Published on: March 1, 2017

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

Area of Science:

Computational Biology
Genomics
Systems Biology

Background:

Cell-cell interaction (CCI) is crucial for tissue microenvironment communication.
Spatial transcriptomics (ST) enables systematic CCI investigation, but existing methods require single-cell resolution, which most ST platforms lack.
Analyzing ST data for CCI involves complex dependencies and multiple hypothesis testing challenges.

Purpose of the Study:

To introduce RECCIPE, a novel computational method for identifying cell signaling interactions in spatial transcriptomics data.
To address the limitations of existing methods by not requiring single-cell resolution and handling complex data structures.
To enable genome-wide screening of gene expression changes attributed to CCIs.

Main Methods:

RECCIPE integrates gene expression, spatial information, and cell type composition.
It employs a multivariate regression framework for analysis.
The method facilitates genome-wide screening for gene expression alterations linked to CCIs.

Main Results:

RECCIPE demonstrates high accuracy on simulated spatial transcriptomics datasets.
The method successfully identified novel biological insights from a mouse model of Alzheimer's disease (AD).
It effectively screens for gene expression changes associated with cell-cell interactions.

Conclusions:

RECCIPE is a valuable new tool for studying cell-cell interactions in spatial transcriptomics data.
The framework advances the analysis of gene expression in multicellular systems, particularly in complex tissues.
It provides a robust approach for understanding the impact of CCI on gene regulation.