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Related Concept Videos

Protein Networks02:26

Protein Networks

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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-protein Interfaces02:04

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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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Protein Complexes with Interchangeable Parts01:57

Protein Complexes with Interchangeable Parts

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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.
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NEMo: An Evolutionary Model With Modularity for PPI Networks.

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    We introduce Network Evolution with Modularity (NEMo), a novel model for biological network evolution. NEMo uniquely incorporates and evolves modular structures, addressing a key limitation in existing duplication-based models.

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    Area of Science:

    • Computational Biology
    • Systems Biology
    • Evolutionary Biology

    Background:

    • Biological networks are complex systems modeled as graphs.
    • Evolutionary events include vertex/edge changes and duplications, with duplications driving genomic evolution.
    • Existing models lack the ability to embody and evolve network modularity.

    Purpose of the Study:

    • To introduce Network Evolution with Modularity (NEMo), a new model that integrates and evolves modular structures.
    • To enable modules to dynamically appear, disappear, merge, and fission within the evolutionary process.
    • To develop and apply measures for comparing modular structures in biological networks.

    Main Methods:

    • Developed the NEMo model based on duplication-driven, edge-level evolutionary events.
    • Incorporated mechanisms for module dynamics (appearance, disappearance, fission, merging).
    • Created quantitative measures to assess and compare network modularity.

    Main Results:

    • NEMo successfully models the evolution of modular biological networks.
    • The model demonstrates dynamic module behavior driven by duplication events.
    • Comparative analyses show NEMo's distinct capabilities in evolving modularity compared to existing models.

    Conclusions:

    • NEMo provides a significant advancement in modeling biological network evolution by incorporating dynamic modularity.
    • The model offers a framework for understanding how modularity arises and is maintained during evolution.
    • The developed measures facilitate robust comparisons of modular structures in biological networks.