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

BMC Bioinformatics · 2017 · Vol. 18(1) · pp. 142–142
Antonio FabregatKonstantinos SidiropoulosGuilherme ViteriOscar FornerPablo Marín-GarcíaVicente ArnauPeter D’EustachioLincoln SteinHenning Hermjakob

Abstract

Through the use of highly optimised, in-memory data structures and algorithms, Reactome has achieved a stable, high performance pathway analysis service, enabling the analysis of genome-wide datasets within seconds, allowing interactive exploration and analysis of high throughput data. The proposed pathway analysis approach is available in the Reactome production web site either via the AnalysisService for programmatic access or the user submission interface integrated into the PathwayBrowser. Reactome is an open data and open source project and all of its source code, including the one described here, is available in the AnalysisTools repository in the Reactome GitHub ( https://github.com/reactome/ ).

Bioinformatics and Genomic NetworksMachine Learning in BioinformaticsAdvanced Proteomics Techniques and ApplicationsComputer scienceDNA microarrayComputational biologyBiologyGeneticsGeneGene expression

MeSH terms

AlgorithmsHumansNucleic AcidsProteinsSoftwareDatabases, FactualComputational Biology

Funding

  • European Bioinformatics Institute
  • National Institutes of Health
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