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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...
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: Jun 29, 2026

Probing High-density Functional Protein Microarrays to Detect Protein-protein Interactions
08:07

Probing High-density Functional Protein Microarrays to Detect Protein-protein Interactions

Published on: August 2, 2015

Physical protein-protein interactions predicted from microarrays.

Ta-Tsen Soong1, Kazimierz O Wrzeszczynski, Burkhard Rost

  • 1Columbia University Center for Computational Biology and Bioinformatics, Columbia University, New York, NY, USA. ts2186@columbia.edu

Bioinformatics (Oxford, England)
|October 3, 2008
PubMed
Summary

We developed a new machine learning method to predict protein physical interactions from microarray data. This approach accurately identifies more interactions than traditional methods, aiding in functional annotation and discovery.

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Identifying Protein-protein Interaction Sites Using Peptide Arrays
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Identifying Protein-protein Interaction Sites Using Peptide Arrays

Published on: November 18, 2014

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Systems Biology

Background:

  • Microarray expression data can reveal functionally associated proteins, but most lack direct physical contact.
  • Predicting direct physical protein-protein interactions from expression data is a significant challenge.
  • Existing methods often struggle to accurately identify direct physical interactions.

Purpose of the Study:

  • To develop and validate a novel machine learning method for predicting direct physical protein interactions from microarray data.
  • To improve the accuracy and scope of protein interaction prediction compared to conventional approaches.
  • To facilitate functional annotation and discovery of novel protein interactions.

Main Methods:

  • Developed a novel machine learning method, specifically a support vector machine (SVM)-based approach, optimized for predicting physical interactions.
  • Validated the SVM method on multiple independent datasets.
  • Applied the method to predict protein interactions in yeast (Saccharomyces cerevisiae).

Main Results:

  • The SVM-based method achieved high accuracy in predicting physical interactions.
  • Our method recovered more experimentally validated physical interactions than a conventional correlation-based approach at similar accuracy levels.
  • Predicted interacting pairs were network-neighbors, indicating utility for functional annotation.
  • Analysis of yeast predictions revealed novel, experimentally verifiable interactions.

Conclusions:

  • The novel machine learning method effectively predicts direct physical protein interactions from microarray data.
  • This approach offers improved performance over traditional methods and aids in identifying novel interactions.
  • The method has the potential to enhance protein interaction annotation within multi-source integrated systems.