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Reactome graph database: Efficient access to complex pathway data.

Antonio Fabregat1,2, Florian Korninger1, Guilherme Viteri1

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Summary
This summary is machine-generated.

Reactome now uses a graph database for biomolecular pathway data, significantly improving access efficiency. This enhancement reduces query times by 93%, offering a high-performance resource for researchers.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Database Management

Background:

  • Reactome is a curated knowledgebase of biomolecular pathways.
  • Traditional relational databases present performance challenges for complex pathway data querying.
  • Efficient data access is crucial for biological pathway databases.

Purpose of the Study:

  • To present the adoption of a graph database for Reactome.
  • To introduce the new ContentService (REST API) for data access.
  • To improve the efficiency and accessibility of Reactome pathway data.

Main Methods:

  • Migrated Reactome data to a Neo4j graph database.
  • Developed a new ContentService (REST API) for data access.
  • Utilized the Cypher query language for efficient data traversal.

Main Results:

  • Achieved a 93% reduction in average query time.
  • Enabled more efficient traversal and knowledge discovery of complex pathway data.
  • Provided programmatic access to Reactome data via a web service.

Conclusions:

  • Graph database technology significantly enhances Reactome's data access efficiency.
  • Neo4j and Cypher offer a high-performance solution for complex biological data.
  • The new system provides a powerful, community-accessible pathway data resource.