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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,...
Ligand Binding Sites02:40

Ligand Binding Sites

Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...
Protein Organization01:24

Protein Organization

Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
The primary structure of a protein is its amino acid sequence.

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Related Experiment Video

Updated: Jul 11, 2026

Mapping Dysfunctional Protein-Protein Interactions in Disease
09:39

Mapping Dysfunctional Protein-Protein Interactions in Disease

Published on: October 24, 2025

Coverage and error models of protein-protein interaction data by directed graph analysis.

Tony Chiang1, Denise Scholtens, Deepayan Sarkar

  • 1EMBL, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. tchiang@ebi.ac.uk

Genome Biology
|September 12, 2007
PubMed
Summary

Researchers analyzed protein interaction data in Saccharomyces cerevisiae using graph and error models. They identified key error traits necessary for understanding the protein interactome and its modules.

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

Published on: March 3, 2015

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Last Updated: Jul 11, 2026

Mapping Dysfunctional Protein-Protein Interactions in Disease
09:39

Mapping Dysfunctional Protein-Protein Interactions in Disease

Published on: October 24, 2025

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:

  • * Systems biology
  • * Computational biology
  • * Molecular biology

Background:

  • * Understanding protein-protein interactions is crucial for deciphering cellular functions.
  • * Large-scale experimental datasets for protein interactions often contain errors, complicating analysis.
  • * Saccharomyces cerevisiae is a model organism widely used for studying fundamental biological processes.

Purpose of the Study:

  • * To assess and characterize error statistics in published large-scale protein interaction datasets for Saccharomyces cerevisiae.
  • * To identify key traits of these errors, including tested interactions, artifacts, and stochastic error rates.
  • * To establish a foundation for accurate estimation of the protein interactome and its modules.

Main Methods:

  • * Application of a directed graph model to represent bait-to-prey systems.
  • * Utilization of a multinomial error model to quantify data inaccuracies.
  • * Systematic analysis of all available large-scale Saccharomyces cerevisiae protein interaction datasets.

Main Results:

  • * Characterization of error statistics based on three distinct traits: tested interactions, false-positive/negative artifacts, and stochastic error rates.
  • * Quantification of the impact of these error traits on the reliability of protein interaction data.
  • * Identification of specific patterns and sources of error within the datasets.

Conclusions:

  • * The characterized error traits are essential prerequisites for robust protein interactome and module estimation.
  • * This work provides a framework for improving the accuracy and reliability of large-scale protein interaction studies.
  • * Understanding and accounting for errors is critical for advancing systems biology research in Saccharomyces cerevisiae.