Do data resources managed by EMBL-EBI and collaborators make a difference to your work? Please take 10 minutes to fill in the annual user survey, and help make the case for why sustaining open data resources is critical for life sciences research.

Survey

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

In the May 2024 issue of Briefings in Bioinformatics, Xu et al. develop an Interpretable Biological Pathway Graph Neural Network (IBPGNET) framework based on Reactome pathway hierarchy to predict regulatory mechanisms that lead to lung adenocarcinoma recurrences. IBPGNET identified two genes of interest and performed in vitro knockdown models for drug sensitivity experimental validation. This study offers an approach for exploring molecular mechanisms underlying recurrence using Reactome’s hierarchical pathway structure.

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

Cite Us!