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Related Experiment Video

Updated: Mar 7, 2026

A Web Tool for Generating High Quality Machine-readable Biological Pathways

A Web Tool for Generating High Quality Machine-readable Biological Pathways

Published on: February 8, 2017

Reactome pathway analysis: a high-performance in-memory approach.

Antonio Fabregat^1,2, Konstantinos Sidiropoulos¹, Guilherme Viteri¹

¹European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, UK.

BMC Bioinformatics

|March 3, 2017

Summary

This summary is machine-generated.

Reactome offers a faster pathway analysis service using optimized in-memory data structures. This enables rapid analysis of large genome-wide datasets, supporting systems biology and biomedical research.

Keywords:

Data structures Over-representation analysis Pathway analysis

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Area of Science:

Bioinformatics
Systems Biology
Computational Biology

Background:

Reactome provides bioinformatics tools for pathway knowledge analysis.
Pathway analysis is crucial for physiological and biomedical research.
Increasing data sample sizes pose performance challenges for analysis methods.

Purpose of the Study:

To present a high-performance, in-memory implementation of the over-representation analysis method.
To optimize pathway analysis for large datasets.

Main Methods:

Implemented over-representation analysis in four steps using specialized data structures.
Utilized a radix tree for efficient identifier lookup.
Employed a graph for modeling biological entities and complexes.
Used a double-linked tree for result aggregation and statistical calculation.

Main Results:

Achieved stable, high-performance pathway analysis.
Enabled analysis of genome-wide datasets within seconds.
Minimized memory footprint through optimized data structures.

Conclusions:

Reactome's optimized approach facilitates interactive exploration of high-throughput data.
The pathway analysis service is accessible via AnalysisService and PathwayBrowser.
Reactome is an open-source project with all code available on GitHub.