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Related Concept Videos

Protein Networks02:26

Protein Networks

4.4K
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,...
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Protein Networks02:26

Protein Networks

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Protein-protein Interfaces02:04

Protein-protein Interfaces

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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...
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Mapping Dysfunctional Protein-Protein Interactions in Disease
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Enriching Human Interactome with Functional Mutations to Detect High-Impact Network Modules Underlying Complex

Hongzhu Cui1, Suhas Srinivasan2, Dmitry Korkin1,2,3

  • 1Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA.

Genes
|November 17, 2019
PubMed
Summary

We developed DIMSUM, a computational framework to identify disease-specific functional modules in biological networks. This method integrates genome-wide association studies and mutation impact for improved disease gene discovery.

Keywords:
GWAScomplex diseasesfunctional annotationmodule detectionnetwork propagationprotein–protein interaction network

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Area of Science:

  • Genomics
  • Systems Biology
  • Bioinformatics

Background:

  • High-throughput omics technologies generate vast biological data, yet understanding complex genetic diseases remains challenging.
  • Biological networks are crucial for deciphering disease mechanisms, but identifying disease-specific modules within the human interactome is difficult.

Purpose of the Study:

  • To present a computational framework, Discovering most IMpacted SUbnetworks in interactoMe (DIMSUM), for enhanced disease module detection.
  • To integrate genome-wide association studies (GWAS) and functional mutation effects into protein-protein interaction (PPI) networks.

Main Methods:

  • DIMSUM incorporates and propagates the functional impact of non-synonymous single nucleotide polymorphisms (nsSNPs) on PPIs.
  • It identifies genes most affected by disruptive mutations and pinpoints the most functionally impactful disease module.

Main Results:

  • DIMSUM yields biologically relevant modules with stronger disease associations compared to state-of-the-art methods.
  • The framework effectively implicates genes influenced by disruptive mutations within the PPI network.

Conclusions:

  • DIMSUM offers a novel computational approach for disease module analysis.
  • This method is expected to become a valuable tool for discovering new disease markers and advancing our understanding of complex genetic diseases.