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SIGNOR 3.0, the SIGnaling network open resource 3.0: 2022 update.

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Summary
This summary is machine-generated.

The SIGNOR 3.0 database offers an upgraded resource for biological signaling pathways. It now features enhanced tools, expanded content with over 33,000 interactions, and new pathway information for improved model building.

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Area of Science:

  • Systems Biology
  • Molecular Biology
  • Bioinformatics

Background:

  • Biological signaling networks are complex and crucial for cellular function.
  • Understanding these networks requires comprehensive and accessible data resources.
  • Previous versions of SIGNOR provided a foundation for mapping causal interactions.

Purpose of the Study:

  • To present the significant upgrades and expanded content of the SIGNOR 3.0 database.
  • To highlight new features enhancing user experience and data analysis capabilities.
  • To provide an updated resource for researchers studying biological signaling pathways.

Main Methods:

  • Manual curation of causal relationships and pathway information.
  • Development of a new website with advanced search and graph visualization tools.
  • Implementation of an 'activity-flow' model for representing signaling events.
  • Inclusion of metabolic reactions and a confidence score for interactions.

Main Results:

  • SIGNOR 3.0 now contains approximately 33,000 manually annotated causal relationships involving over 8900 biological entities.
  • The database includes expanded pathway information, notably for SARS-CoV-2 infection, neurodevelopment, synaptic transmission, and metabolism.
  • New features include an improved user interface, advanced search functionalities, and a confidence scoring system for interactions.

Conclusions:

  • SIGNOR 3.0 represents a substantially enhanced resource for exploring and analyzing biological signaling networks.
  • The expanded content and improved tools facilitate the construction of dynamic and predictive biological models.
  • This updated repository supports research across various biological domains, including disease mechanisms and fundamental cellular processes.