reactome

Overview

Reactome is the world’s leading open-source, open access, manually curated and peer-reviewed knowledgebase of human biological pathways. It provides comprehensive, integrated representation of biological processes from molecular details to systems-level phenomena. Developed collaboratively by an international consortium of research institutions and databases, Reactome combines expert curation with data integration tools to create a foundation for computational biology research, systems biology analysis, and understanding human biology and disease.

The Reactome pathway database describes reactions and biological processes in a machine-readable format, integrating knowledge of how genes and their products participate in organized biological processes. This enables comparative genomics, drug target identification, functional genomics analysis, and personalized medicine approaches.

Scope and Coverage

Pathway Content

Reactome covers human biological pathways across multiple domains:

• Signal Transduction: Growth factors, cytokine signaling, receptor cascades
• Metabolism: Metabolic pathways including carbohydrate, lipid, and protein metabolism
• Immunity: Innate and adaptive immune responses, complement activation
• Hemostasis: Blood coagulation and platelet aggregation cascades
• DNA Replication and Repair: DNA synthesis, repair mechanisms, and cell cycle
• Gene Expression: Transcription, translation, and post-translational modifications
• Transport: Vesicular transport, ion transport, and membrane trafficking
• Cell-Cell Interaction: Adhesion, communication, and junction organization
• Neuronal Systems: Neurotransmission, synaptic plasticity, neurodegeneration

Species Coverage

While primarily curated for human pathways:

• Primary focus: Homo sapiens (NCBITaxon:9606)
• Secondary focus: Mus musculus (house mouse, NCBITaxon:10090)
• Cross-species mapping: Ortholog-based projections for other organisms via Ensembl

Data Scale

• Over 12,000 unique human reactions and pathways
• More than 250,000 individual reaction instances
• Coverage of approximately 10,000+ human genes
• Integration with multiple external databases and ontologies

Data Organization and Structure

Pathway Hierarchies

Reactome organizes biological knowledge in hierarchical pathways:

1. Top-level pathways representing major biological domains
2. Intermediate-level processes showing specific biological outcomes
3. Reaction-level detail describing specific molecular interactions

Reaction Representation

Each reaction captures:

• Input entities: Proteins, small molecules, complexes involved
• Catalysts: Enzymes or proteins enabling the reaction
• Output: Products of the reaction
• Requirements: Cofactors, compartments, conditions
• Regulation: Positive and negative regulatory mechanisms

Integration with External Data

Reactome integrates and cross-references:

• Gene information: HGNC, Ensembl, NCBI Gene
• Protein data: UniProtKB, PDB structures, InterPro
• Chemical compounds: ChEBI, PubChem
• Disease information: Disease Ontology, Ensembl phenotypes
• Gene Ontology: GO terms for functional annotation
• Literature: PubMed references for evidence traceability

Data Access and Products

Download Formats

Reactome is available in multiple standardized formats:

1. BioPAX Format: Standard pathway data exchange format
   • Supports pathway representation and computational analysis
   • Compatible with pathway analysis tools and integrated models
2. SBML Format: Systems Biology Markup Language
   • For computational modeling and systems biology applications
   • Includes detailed kinetic and mathematical information
3. Graph Database (Neo4j): Native graph representation
   • Full interactive pathway exploration
   • Supports complex relationship queries and analysis
4. RDF/OWL Format: Semantic web representation
   • For knowledge graph integration and reasoning
   • Linked Data principles with dereferenceable URIs
5. TSV/CSV Data: Tabular format for spreadsheet analysis
   • Curated protein complex compositions
   • Pathway-gene associations and mappings
6. JSON: Modern programmatic data format
   • RESTful API access
   • Suitable for web applications and visualization

Access Methods

• Website Interface: Interactive pathway browser with visual exploration
• REST API: Programmatic access with JSON responses
• Graph Database: Direct Neo4j graph queries
• FTP/Download: Bulk data downloads in various formats
• SPARQL Endpoint: Semantic web query language support
• R/Bioconductor: ReactomePA and ReactomeDB packages

Curation and Quality Assurance

Peer Review and Validation

• Expert Curation: Pathways curated by domain specialists
• Peer Review: Multiple rounds of review for quality assurance
• Evidence Tracking: PubMed references for all assertions
• Version Control: Detailed change history and release notes

Update Frequency

• Regular quarterly releases with new pathway curation
• Continuous updates to human pathway knowledge
• Maintenance of links to external databases
• Sustainability through international consortium support

Integration and Interoperability

Standards Compliance

• W3C Standards: RDF, OWL, SPARQL compatibility
• Systems Biology: SBML and BioPAX compliance
• Data Formats: Standard exchange formats (TSV, JSON, XML)
• Web Standards: REST API, HTTP, linked data

Cross-Database Integration

Reactome integrates with:

• Pathway Databases: WikiPathways, KEGG, PANTHER
• Protein Resources: STRING, UniProt, Ensembl
• Ontologies: Gene Ontology, Disease Ontology, ChEBI
• Knowledge Graphs: Various biomedical knowledge graphs

Canonical Pathway Mapping

Reactome provides canonical human pathway representations that serve as:

• Reference pathways for cross-species comparative analysis
• Foundation for personalized pathway analysis
• Basis for pathway-based drug target identification
• Framework for systems biology modeling

Use Cases and Applications

Research Applications

• Drug Discovery: Identifying therapeutic targets and mechanisms of action
• Functional Genomics: Understanding gene function in biological context
• Systems Biology: Modeling complex biological networks and feedback loops
• Precision Medicine: Patient-specific pathway analysis
• Biomarker Discovery: Identifying pathway-based molecular signatures
• Target Validation: Understanding pathway context for therapeutic targets

Clinical Applications

• Disease Mechanism Analysis: Understanding molecular basis of diseases
• Variant Effect Prediction: Interpreting genetic variants in pathway context
• Therapy Response Prediction: Pathway-based prediction of drug response
• Clinical Trial Design: Identifying relevant pathway biomarkers

Data Integration

• Multi-Omics Analysis: Contextualizing omics data in pathways
• Expression Analysis: Understanding expression changes within pathway context
• Mutation Analysis: Interpreting genetic alterations in pathway networks
• Knowledge Synthesis: Aggregating pathway knowledge across studies

Computational Biology

• Pathway Analysis: Over-representation and enrichment analysis
• Network Analysis: Graph-based pathway analysis and visualization
• Systems Modeling: Construction of computational biological models
• Knowledge Curation: Structured pathway representation for AI/ML

Leadership and Community

Reactome Consortium

International collaboration between:

• New York University School of Medicine: Lead institution
• European Bioinformatics Institute (EMBL-EBI): Co-lead
• Ontario Institute for Cancer Research: Contributing institution
• University of Toronto: Contributing institution

Scientific Steering Committee

Oversees strategic direction and quality standards for the resource.

Community Contributions

• Open community curation model
• Expert review process
• Integration of externally-curated pathway data
• Collaborative enhancement of pathway coverage

Citation and Usage

All Reactome data is freely available under Creative Commons Attribution 4.0 (CC BY 4.0) license.

Recommended Citations

For Reactome knowledgebase use: “Gillespie ME, et al. The Reactome pathway knowledgebase 2022. Nucleic Acids Research. 2022;50(D1):D687-D692. https://doi.org/10.1093/nar/gkab1028”

For specific pathway data: “Reactome: A Knowledgebase of Biological Pathways. Available at: https://reactome.org”

Key Resources

• Website: https://reactome.org/
• Pathway Browser: https://reactome.org/PathwayBrowser/
• REST API: https://reactome.org/ContentService/
• FTP Server: https://reactome.org/download/
• GitHub Repository: https://github.com/reactome
• Citation Instructions: https://reactome.org/about/cite

Standards and Compliance

• Peer-Reviewed: Published in Nucleic Acids Research annually
• Open Access: CC BY 4.0 licensing with no access restrictions
• Version Control: Detailed release notes and change tracking
• Quality Standards: Expert curation with evidence documentation
• FAIR Principles: Designed for Findability, Accessibility, Interoperability, Reusability
• Sustainability: International consortium with stable funding

Additional Notes

This registry includes alternative translations of Reactome data:

• Direct representations from BioPAX format
• Biopragmatics conversion and mappings
• Multiple graph database distributions
• Integrations with knowledge graph frameworks

For more information on Reactome’s sister resources and related projects, see also the related entries in this registry.