Pathway Browser

Visualize and interact with Reactome biological pathways

Analysis Tools

Merges pathway identifier mapping,
over-representation, and expression analysis

ReactomeFIViz

Designed to find pathways and network patterns related to cancer and other types of diseases

Documentation

Information to browse the database and use its principal tools for data analysis

Reactome Research Spotlight

[July 1, 2024] In their May 2024 Nature Communications paper, Chen et al. used data simulated based on Reactome pathways to validate their Functional Representation of Gene Signatures (FRoGS) algorithm, a deep learning-based approach that was designed to improve the accuracy of drug target predictions by addressing limitations of gene identity-based pathway analysis

ARCHIVE

Why Reactome

Reactome is a free, open-source, curated and peer-reviewed pathway database. Our goal is to provide intuitive bioinformatics tools for the visualization, interpretation and analysis of pathway knowledge to support basic research, genome analysis, modeling, systems biology and education. 

European Bioinformatics Institute (EMBL-EBI)
NYU Langone Health
Oregon Health & Science University
Ontario Institute for Cancer Research

The development of Reactome is supported by grants from the US National Institutes of Health (U24 HG012198) and the European Molecular Biology Laboratory.

Version 89 released on June 16th, 2024

2,711

Human Pathways

15,326

Reactions

11,495

Proteins

2,127

Small Molecules

1,047

Drugs

38,895

Literature References

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