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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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Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
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Signaling cascades usually lack linearity. Multiple pathways interact and regulate one another, allowing cells to integrate and respond to diverse environmental stimuli.
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The extracellular matrix or ECM holds cells together to form a tissue and allows the cells within the tissue to communicate. ECM comprises proteins such as fibronectin, collagen, laminin, etc. The most abundant protein in this space is collagen. Collagen fibers are interwoven with carbohydrate-containing protein molecules called proteoglycans. ECM allows cell migration and provides a structural scaffold at cell adhesion that anchors the cell when the extracellular matrix proteins interact with...
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A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
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Interactomes in the era of deep learning.

Joana Pereira1,2, Torsten Schwede1,2

  • 1Biozentrum, University of Basel, Basel, Switzerland.

Science (New York, N.Y.)
|December 9, 2021
PubMed
Summary

Deep learning offers a detailed view of the yeast protein interactome. This approach captures a precise moment of protein interactions within yeast cells.

Area of Science:

  • Proteomics
  • Systems Biology
  • Computational Biology

Background:

  • Understanding protein interactions is crucial for deciphering cellular mechanisms.
  • The yeast protein interactome is a complex network that requires advanced analytical methods.
  • Previous methods have limitations in providing a dynamic or comprehensive view.

Purpose of the Study:

  • To apply deep learning techniques to map the yeast protein interactome.
  • To generate a high-resolution snapshot of protein interactions in yeast.
  • To provide a novel computational approach for interactome analysis.

Main Methods:

  • Utilized deep learning algorithms to analyze large-scale protein interaction data.
  • Developed a computational model to predict and visualize protein interactions.

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  • Focused on the Saccharomyces cerevisiae (yeast) model organism.

    • Main Results:

    • Generated an 'atomic snapshot' of the yeast protein interactome.
    • The deep learning model successfully identified numerous protein-protein interactions.
    • Provided unprecedented detail in visualizing the interactome network.

    Conclusions:

    • Deep learning is a powerful tool for dissecting complex biological networks.
    • This study offers a valuable resource for yeast systems biology research.
    • The methodology can be extended to study interactomes in other organisms.