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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 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...
Protein Complex Assembly02:41

Protein Complex Assembly

Proteins can form homomeric complexes with another unit of the same protein or heteromeric complexes with different types.  Most protein complexes self-assemble spontaneously via ordered pathways, while some proteins need assembly factors that guide their proper assembly. Despite the crowded intracellular environment, proteins usually interact with their correct partners and form functional complexes.
Many viruses self-assemble into a fully functional unit using the infected host cell to...

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Related Experiment Video

Updated: Jun 16, 2026

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
06:50

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Published on: January 26, 2024

Predicting protein complex membership using probabilistic network reliability.

Saurabh Asthana1, Oliver D King, Francis D Gibbons

  • 1Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts 02115, USA.

Genome Research
|May 14, 2004
PubMed
Summary
This summary is machine-generated.

This study introduces a probabilistic network model to improve protein complex inference by accounting for the quantity and quality of protein-protein interaction evidence, moving beyond simple presence/absence data.

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A Protocol for Computer-Based Protein Structure and Function Prediction
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A Protocol for Computer-Based Protein Structure and Function Prediction

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Related Experiment Videos

Last Updated: Jun 16, 2026

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
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Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Published on: January 26, 2024

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A Protocol for Computer-Based Protein Structure and Function Prediction
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A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Area of Science:

  • Bioinformatics
  • Systems Biology
  • Network Science

Background:

  • Protein-protein interactions (PPIs) form complex networks crucial for cellular functions.
  • Large-scale PPI studies are prone to errors, varying by method.
  • Current PPI networks often treat interactions as binary (present/absent), ignoring evidence reliability.

Purpose of the Study:

  • To develop a probabilistic network model for more accurate protein complex inference.
  • To address the limitations of binary interaction data in PPI networks.
  • To leverage the quantity and quality of evidence for improved network analysis.

Main Methods:

  • Utilized a probabilistic network model to represent PPIs.
  • Incorporated an algorithm for evaluating reliability, adapted from communication networks.
  • Applied the model to infer membership in a partially known protein complex.

Main Results:

  • Demonstrated improved inference of protein complex membership using the probabilistic model.
  • Showcased the utility of considering evidence quantity and quality over binary interaction data.
  • Validated the approach for analyzing error-prone PPI network data.

Conclusions:

  • Probabilistic network models offer a more robust approach to analyzing PPI data.
  • Accounting for evidence reliability enhances the accuracy of biological network inference.
  • This method holds potential for improving our understanding of protein complex organization and function.