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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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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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Predicted rat interactome database and gene set linkage analysis.

Yu-Tian Tao1, Xiao-Bao Ding1, Jie Jin1

  • 1Institute of Big data and Artificial Intelligence in Medicine, School of Electronics & Information Engineering, Taizhou University, 1139 Shifu Avenue, Taizhou, 318000, China.

Database : the Journal of Biological Databases and Curation
|November 20, 2020
PubMed
Summary
This summary is machine-generated.

The Predicted Rat Interactome Database (PRID) offers a comprehensive resource for studying rat models of human disease. This database aids in understanding gene interactions for improved molecular pharmacology and drug discovery research.

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Area of Science:

  • Biomedical Research
  • Genomics
  • Bioinformatics

Background:

  • Rattus norvegicus (rat) is a crucial animal model for human diseases due to physiological similarities and size.
  • Rat models are extensively used in drug discovery for efficacy and toxicity assessments.
  • Existing tools lack comprehensive functional gene interaction data for rat molecular studies.

Purpose of the Study:

  • To develop a high-quality predicted functional gene interactions database for rats.
  • To facilitate molecular pharmacology and drug discovery research using rat models.
  • To provide a resource for gene set linkage analysis (GSLA).

Main Methods:

  • Integrated functional gene association data from 10 public databases.
  • Inferred 305,939 putative functional gene associations for the rat interactome.
  • Developed the Predicted Rat Interactome Database (PRID).

Main Results:

  • PRID contains a substantial number of predicted functional gene associations, potentially covering 13.02% of all rat protein interactions.
  • Over 52% of these associations may represent direct protein interactions.
  • Gene Set Linkage Analysis (GSLA) using PRID provided more precise and informative annotations compared to GO and DAVID analysis.

Conclusions:

  • PRID serves as a valuable reference interactome for hypothesis formulation in molecular mechanism studies.
  • GSLA based on PRID enhances understanding of physiological mechanisms and generates testable hypotheses.
  • PRID offers superior insights for rat molecular research compared to existing annotation tools.