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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 Families02:47

Protein Families

Protein families are groups of homologous proteins; that is, they have similarities in amino acid sequences and three-dimensional structures. Protein families usually occur because of gene duplication, where an additional copy of a gene is inserted into the genome of an organism.   Mutations that change the amino acids but still allow the protein to be properly synthesized, will lead to new protein family members.   If these new proteins contain similar amino acids in key locations, protein...
Protein Families02:47

Protein Families

Protein families are groups of homologous proteins; that is, they have similarities in amino acid sequences and three-dimensional structures. Protein families usually occur because of gene duplication, where an additional copy of a gene is inserted into the genome of an organism.   Mutations that change the amino acids but still allow the protein to be properly synthesized, will lead to new protein family members.   If these new proteins contain similar amino acids in key locations, protein...

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A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

A novel function prediction approach using protein overlap networks.

Shide Liang1, Dandan Zheng, Daron M Standley

  • 1Systems Immunology Lab, Immunology Frontier Research Center, Osaka University, Suita, Osaka 565-0871, Japan. shideliang@ifrec.osaka-u.ac.jp

BMC Systems Biology
|July 23, 2013
PubMed
Summary
This summary is machine-generated.

We developed a protein overlap network (PON) model for predicting protein functions. This network approach significantly improved prediction accuracy compared to random methods, offering a reliable tool for biological research.

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Last Updated: May 9, 2026

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Network construction is crucial for protein function prediction.
  • Protein Overlap Networks (PONs) were developed using domain sharing data from the InterPro database.
  • PONs were built for yeast, fly, worm, and human genomes.

Purpose of the Study:

  • To establish a reliable network model for protein function prediction.
  • To evaluate the effectiveness of PONs in predicting gene ontology (GO) terms.
  • To assess prediction performance across different species and genome sizes.

Main Methods:

  • Constructed PONs where proteins are nodes connected by shared domains.
  • Utilized GO term frequencies of neighboring proteins for function prediction.
  • Employed a composite PON across four species to enhance prediction accuracy.
  • Analyzed manually annotated GO terms for further refinement.

Main Results:

  • PONs demonstrated an average success rate of 34.3% and coverage of 43.9%.
  • A composite PON improved prediction to 37.9% success and 51.3% coverage.
  • Random control yielded only 7.0% success rate.
  • Predictions using second-layer nodes achieved >30% success and coverage, even for small genomes.

Conclusions:

  • PONs exhibit dense modular structures with sparse long-range connections.
  • Developed multiple effective approaches for protein function prediction based on PONs.
  • The PON model offers a robust framework for advancing network-based protein function prediction.