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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 Networks

Protein Networks

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...

Protein-Protein Interfaces

Protein-Protein Interfaces

Proteomics

Proteomics

A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...

Protein Complexes with Interchangeable Parts

Protein Complexes with Interchangeable Parts

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Related Experiment Video

Updated: Dec 14, 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

Proteinarium: Multi-sample protein-protein interaction analysis and visualization tool.

David Armanious¹, Jessica Schuster², George A Tollefson³

¹Department of Computer Science, Brown University, Providence, RI, United States of America.

|July 24, 2020

Summary

This summary is machine-generated.

Complex diseases may arise from shared gene network variants within patient subgroups. Proteinarium, a protein-protein interaction tool, identifies these patient clusters, enhancing disease subtyping and discovery.

Keywords:

Data visualization Multi-sample Networks Protein-protein interactions Software

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Last Updated: Dec 14, 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

Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay PCA in Living Cells

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Published on: March 3, 2015

Identifying Protein-protein Interaction Sites Using Peptide Arrays

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Published on: November 18, 2014

Area of Science:

Genomics
Systems Biology
Bioinformatics

Background:

Complex diseases often involve intricate genetic architectures.
Identifying patient subgroups with shared genetic underpinnings is crucial for understanding disease heterogeneity.

Purpose of the Study:

To develop and validate Proteinarium, a novel computational tool for identifying patient clusters based on shared gene networks.
To enhance the analysis of complex diseases by uncovering patient subgroups with specific genetic network profiles.

Main Methods:

Proteinarium utilizes protein-protein interaction (PPI) data from STRING interactome.
Dijkstra's algorithm constructs sample-specific PPI networks.
Pairwise similarity scores and network clustering identify patient subgroups.

Main Results:

Proteinarium successfully identified significant patient clusters with unique gene networks in reanalyzed datasets.
The tool enhanced findings from previous studies with modest outcomes.
A layered graph visualization aids in understanding clustered PPI networks.

Conclusions:

Proteinarium provides a robust method for dissecting complex diseases at the network level.
The tool facilitates the discovery of novel patient subgroups and potential therapeutic targets.
This approach advances the understanding of genotype-phenotype relationships in complex diseases.