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Protein Networks

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...

Protein-protein Interfaces

Protein-protein Interfaces

Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...

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Related Experiment Video

Updated: Jul 31, 2025

Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation

Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation

Published on: August 21, 2019

Cell annotation using scRNA-seq data: A protein-protein interaction network approach.

Daniela Senra¹, Nara Guisoni¹, Luis Diambra¹

¹Centro Regional de Estudios Genómicos, Universidad Nacional de La Plata, CONICET, Argentina.

|May 2, 2023

Summary

This summary is machine-generated.

This study introduces a new method using protein-protein interaction networks to analyze biological pathways in single-cell RNA sequencing (scRNA-seq) data. The approach reveals diverse cellular functions within tumor cells, aiding in disease research.

Keywords:

Biological Processes Breast cancer Cell annotation ORIGINS2 Protein-protein interaction networks scRNA-seq

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Last Updated: Jul 31, 2025

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Area of Science:

Computational biology
Genomics
Systems biology

Background:

Pathway analysis is crucial for interpreting single-cell RNA sequencing (scRNA-seq) data, identifying active cellular processes in individual cells.
Dysregulated cellular functions are implicated in various human disorders, including cancer and autoimmune diseases.

Purpose of the Study:

To extend a protein-protein interaction network-based framework for quantifying pathway activity beyond pluripotency to any biological process or gene list.
To provide a systems-level characterization of pathway activities across cell types for analyzing healthy and diseased conditions.
To illustrate the method's application in analyzing biological processes in healthy and cancerous breast samples.

Main Methods:

Implementation of a protein-protein interaction network-based approach to quantify biological process activity.
Extension of a previously developed framework for scRNA-seq data analysis.
Application of the methodology to analyze healthy and cancer breast tissue samples.

Main Results:

The extended approach successfully quantifies the activity of diverse biological processes from scRNA-seq data.
Analysis of breast cancer samples revealed that tumor cells, even within a single UMAP cluster, maintain distinct active biological programs.
The method demonstrated utility in characterizing pathway heterogeneity within cell populations.

Conclusions:

The developed methodology offers a broadly applicable tool for systems-level pathway analysis in various biological contexts, including disease.
This approach can be utilized for cell annotation in scRNA-seq studies.
The methodology is available as a free R package for broader scientific use.