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Related Concept Videos

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 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 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 4, 2026

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

Ensemble non-negative matrix factorization methods for clustering protein-protein interactions.

Derek Greene1, Gerard Cagney, Nevan Krogan

  • 1School of Computer Science and Informatics, University College Dublin, Dublin, Ireland. derek.greene@ucd.ie

Bioinformatics (Oxford, England)
|June 17, 2008
PubMed
Summary
This summary is machine-generated.

This study introduces an Ensemble non-negative matrix factorization (NMF) algorithm for protein interaction data. The method enhances clustering to reveal protein complexes and predict functions for uncharacterized proteins.

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Last Updated: Jul 4, 2026

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

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Published on: March 3, 2015

Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation
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Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation

Published on: August 21, 2019

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Area of Science:

  • Computational Biology
  • Bioinformatics
  • Systems Biology

Background:

  • Analyzing large-scale protein interaction data is crucial for understanding cellular organization.
  • Identifying higher-order protein assemblies from interaction networks is a key challenge.
  • Traditional hierarchical clustering methods have limitations in capturing complex biological structures.

Purpose of the Study:

  • To develop a novel algorithm for improved clustering of protein interaction data.
  • To create a 'soft' hierarchy of clusters for more informative analysis.
  • To enhance the discovery of protein complexes and functional assignments.

Main Methods:

  • Proposed a new Ensemble non-negative matrix factorization (NMF) algorithm.
  • Aggregated diverse matrix factorizations for robust clustering.
  • Applied the algorithm to high-quality yeast protein interaction data.

Main Results:

  • The Ensemble NMF algorithm effectively identifies small, localized structures in protein interaction data.
  • Discovered known functional groupings of protein complexes.
  • Successfully assigned putative functions to uncharacterized proteins, such as YNR024W, potentially linking it to the exosome.

Conclusions:

  • Ensemble NMF provides a more informative approach to clustering protein interaction networks.
  • The algorithm aids in identifying protein complexes and predicting protein functions.
  • This method advances the analysis of large-scale biological interaction data.