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Related Concept Videos

Protein Networks02:26

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 Networks02:26

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 Interfaces02:04

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 polypeptide...
Protein-Protein Interfaces02:04

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 polypeptide...
Proteomics01:33

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 proteomics...

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Related Experiment Video

Updated: May 15, 2026

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
07:28

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

ProteinNetworkSight: a user-friendly platform for transforming co-expression patterns into actionable therapeutic

Omri Nahor1, Nitzan Migdal1, Ayelet Gibli1

  • 1Software Engineering Department, School of Software and Electrical Engineering, Azrieli College of Engineering, Jerusalem 9103501, Israel.

Nucleic Acids Research
|May 14, 2026
PubMed
Summary
This summary is machine-generated.

ProteinNetworkSight enables simultaneous analysis of multiple biological patterns from complex datasets. This tool visualizes distinct protein-protein interaction networks and identifies therapeutic targets for personalized medicine.

More Related Videos

Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation
07:57

Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation

Published on: August 21, 2019

Related Experiment Videos

Last Updated: May 15, 2026

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
07:28

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation
07:57

Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation

Published on: August 21, 2019

Area of Science:

  • Systems Biology
  • Computational Biology
  • Bioinformatics

Background:

  • Modern systems biology struggles to analyze multiple feature vectors from quantitative techniques simultaneously.
  • Computational pipelines often generate distinct patterns, but current tools force one-by-one analysis or data merging, losing critical information.
  • Existing web servers are ill-equipped to handle high-dimensional data, hindering the analysis of diverse patient subgroups.

Purpose of the Study:

  • To introduce a novel web server architecture for simultaneous multi-pattern analysis in systems biology.
  • To overcome the limitations of current tools in analyzing high-dimensional biological data.
  • To facilitate the identification of personalized therapeutic strategies by preserving disease heterogeneity.

Main Methods:

  • Developed ProteinNetworkSight, a web server accepting multi-column tables for simultaneous vector analysis.
  • Transformed input vectors into discrete, interactive protein-protein interaction networks in a single run.
  • Implemented a batch vector architecture for side-by-side visualization of network topologies and calculated a composite perturbation score.

Main Results:

  • ProteinNetworkSight allows simultaneous analysis and visualization of multiple distinct protein-protein interaction network topologies.
  • The server preserves disease heterogeneity by analyzing patterns independently.
  • Identified key protein nodes specific to each pattern and mapped FDA-approved drugs to these targets.

Conclusions:

  • ProteinNetworkSight offers a novel solution for simultaneous multi-pattern analysis, addressing a key bottleneck in systems biology.
  • The tool facilitates the rapid design of personalized combinatorial therapies by identifying actionable therapeutic targets.
  • This approach enhances the analysis of complex biological data and supports precision medicine initiatives.