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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...
Protein Complexes with Interchangeable Parts01:57

Protein Complexes with Interchangeable Parts

Groups of proteins may form a complex where each protein in this complex has a different role in the overall execution of the complex’s function. Often some of the proteins in the complex can be replaced by a closely related variant to give a complex that contains many of the same components yet is functionally distinct.
The SCF ubiquitin ligase is a protein complex of five individual proteins. This complex attaches ubiquitin to other target proteins to mark them for degradation. In order to...
Protein Complexes with Interchangeable Parts01:57

Protein Complexes with Interchangeable Parts

Groups of proteins may form a complex where each protein in this complex has a different role in the overall execution of the complex’s function. Often some of the proteins in the complex can be replaced by a closely related variant to give a complex that contains many of the same components yet is functionally distinct.
The SCF ubiquitin ligase is a protein complex of five individual proteins. This complex attaches ubiquitin to other target proteins to mark them for degradation. In order to...

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Related Experiment Video

Updated: Jul 2, 2026

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

QNet: a tool for querying protein interaction networks.

Banu Dost1, Tomer Shlomi, Nitin Gupta

  • 1Computer Science and Engineering, University of California, San Diego, California, USA. bdost@cs.ucsd.edu

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|August 19, 2008
PubMed
Summary

This study introduces QNet, a computational tool for querying molecular pathways in biological networks. QNet efficiently identifies complex pathway structures, enabling large-scale cross-species comparisons of protein complexes.

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Related Experiment Videos

Last Updated: Jul 2, 2026

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

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

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Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay (PCA) in Living Cells
08:38

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

Published on: March 3, 2015

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Systems Biology

Background:

  • Molecular interaction databases are crucial for studying evolutionary pathways.
  • Current computational methods for querying these pathways are limited to simple paths or forests.
  • Efficiently querying complex molecular network structures remains a significant challenge.

Purpose of the Study:

  • To extend the capabilities of pathway querying to trees and graphs of bounded treewidth.
  • To develop and implement an efficient tool for identifying non-exact pathway matches.
  • To enable large-scale cross-species comparisons of protein complexes.

Main Methods:

  • Utilized the color coding technique for efficient querying of molecular pathways.
  • Developed QNet, a computational tool for tree queries in biological networks.
  • Tested QNet's performance using simulations and real-world protein interaction network data.

Main Results:

  • QNet can search queries with up to nine proteins in seconds on current networks.
  • QNet outperforms traditional sequence-based search methods.
  • The first large-scale cross-species comparison of protein complexes was performed using QNet, revealing strong conservation between yeast and fly networks.

Conclusions:

  • QNet significantly advances the ability to query complex molecular pathways and networks.
  • The tool facilitates efficient mining of protein interaction networks for evolutionary and comparative analyses.
  • Demonstrated strong evolutionary conservation of protein complexes between yeast and fly species.