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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,...
Conserved Binding Sites01:49

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...
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: May 25, 2026

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
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Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Published on: June 20, 2025

Using ensemble methods to deal with imbalanced data in predicting protein-protein interactions.

Yongqing Zhang1, Danling Zhang, Gang Mi

  • 1College of Computer Science, Sichuan University, Chengdu 610065, PR China.

Computational Biology and Chemistry
|January 31, 2012
PubMed
Summary

Predicting protein-protein interactions (PPIs) is challenging due to imbalanced data. New ensemble methods effectively address this, achieving high accuracy in PPI prediction.

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Published on: June 20, 2025

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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

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Proteomics

Background:

  • Protein-protein interactions (PPIs) are crucial for cellular processes.
  • Predicting PPIs is hindered by imbalanced datasets, where interacting pairs are rare.
  • This imbalance poses a significant challenge for developing accurate predictive models.

Purpose of the Study:

  • To introduce novel ensemble methods for addressing data imbalance in PPI prediction.
  • To enhance the accuracy and reliability of computational PPI prediction.
  • To provide effective solutions for the prevalent imbalanced data problem in bioinformatics.

Main Methods:

  • Developed two ensemble methods combining based-cluster under-sampling and fusion classifiers.
  • Utilized a dataset from the Database of Interacting Proteins (DIP) for evaluation.
  • Employed 10-fold cross-validation to rigorously assess model performance.

Main Results:

  • All developed prediction models achieved an Area Under the Curve (AUC) of approximately 95%.
  • The ensemble classifiers demonstrated high effectiveness in predicting PPIs.
  • The study validated the efficacy of ensemble methods for PPI prediction with imbalanced data.

Conclusions:

  • Ensemble methods are highly effective for predicting protein-protein interactions, especially with imbalanced datasets.
  • The proposed techniques offer a robust solution to a common challenge in bioinformatics.
  • The developed software and datasets are freely available for research use.