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Pathway Browser

Visualize and interact with Reactome biological pathways

Analysis Tools

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


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


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.


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


Human Pathways






Small Molecules




Literature References

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