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Cited by 5,605Bioinformatics and Genomic NetworksBiomedical Text Mining and OntologiesGene Regulatory Network Analysis

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The Reactome pathway Knowledgebase

Open access
Fabregat, Antonio, Sidiropoulos, Konstantinos, Garapati, Phani, Gillespie, Marc, Hausmann, Kerstin, Haw, Robin, Jassal, Bijay, Jupe, Steven, Korninger, Florian, McKay, Sheldon, Matthews, Lisa, May, Bruce, Milacic, Marija, Rothfels, Karen, Shamovsky, Veronica, Webber, Marissa, Weiser, Joel, Williams, Mark, Wu, Guanming, Stein, Lincoln, Hermjakob, Henning, D'Eustachio, Peter·2016·Nucleic Acids Research
DOI 10.1093/nar/gkv1351PMC PMC4702931
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Abstract

The Reactome Knowledgebase (www.reactome.org) provides molecular details of signal transduction, transport, DNA replication, metabolism and other cellular processes as an ordered network of molecular transformations-an extended version of a classic metabolic map, in a single consistent data model. Reactome functions both as an archive of biological processes and as a tool for discovering unexpected functional relationships in data such as gene expression pattern surveys or somatic mutation catalogues from tumour cells. Over the last two years we redeveloped major components of the Reactome web interface to improve usability, responsiveness and data visualization. A new pathway diagram viewer provides a faster, clearer interface and smooth zooming from the entire reaction network to the details of individual reactions. Tool performance for analysis of user datasets has been substantially improved, now generating detailed results for genome-wide expression datasets within seconds. The analysis module can now be accessed through a RESTFul interface, facilitating its inclusion in third party applications. A new overview module allows the visualization of analysis results on a genome-wide Reactome pathway hierarchy using a single screen page. The search interface now provides auto-completion as well as a faceted search to narrow result lists efficiently.

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Registry

Crossref · 10.1093/nar/gkv1351

Cites

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Figures

Figure 1. Pathway Overview. The entire pathways overview map (A). The RAF/MAP kinase cascade pathway is highlighted to show its involvement in multiple bursts (B). A zoomed-in view of the Metabolism burst showing individual subpathway groups (C).
Figure 1. Pathway Overview. The entire pathways overview map (A). The RAF/MAP kinase cascade pathway is highlighted to show its involvement in multiple bursts (B). A zoomed-in view of the Metabolism burst showing individual subpathway groups (C).CC BY · PubMed Central
Figure 2. Diagram viewer. The central panel shows details of reactions and participating molecules in the nine-step process of ubiquinol (ubiquinol-10, Q10H2) biosynthesis. Buttons around the panel support functions including panning and zooming (lower right), changing the view (upper left) and downloading a snapshot of the pathway (upper right).
Figure 2. Diagram viewer. The central panel shows details of reactions and participating molecules in the nine-step process of ubiquinol (ubiquinol-10, Q10H2) biosynthesis. Buttons around the panel support functions including panning and zooming (lower right), changing the view (upper left) and downloading a snapshot of the pathway (upper right).CC BY · PubMed Central
Figure 3. Pathway browser view centred on the ‘gene expression’ top-level pathway. Access to subpathways is provided via the hierarchical display of events on the left and by clicking on event nodes in the pathway display (viewport). Details for the selected event are shown in the panel under the pathway display. Buttons at the right of the top bar show the current version of our software (3.0) with access to our Github software repository, and the current version of our data (release 54). A button in the top bar provide access to the analysis tools (see below, Figure 4). Clicking on the layout buttons closes and re-opens the hierarchical display and details panels. The ‘tour’ button provides access to a brief video tour of the main features of the web site. Clicking on the gearwheel icon in the upper right corner of the pathway diagram provides access to a tool to customize diagram colouring and to an ‘About …’ pop-up that briefly describes pathway diagram features and contains a link to the detailed users’ guide. (This guide is also accessible via the ‘documentation’ drop-down menu at the top of the home page).
Figure 3. Pathway browser view centred on the ‘gene expression’ top-level pathway. Access to subpathways is provided via the hierarchical display of events on the left and by clicking on event nodes in the pathway display (viewport). Details for the selected event are shown in the panel under the pathway display. Buttons at the right of the top bar show the current version of our software (3.0) with access to our Github software repository, and the current version of our data (release 54). A button in the top bar provide access to the analysis tools (see below, Figure 4). Clicking on the layout buttons closes and re-opens the hierarchical display and details panels. The ‘tour’ button provides access to a brief video tour of the main features of the web site. Clicking on the gearwheel icon in the upper right corner of the pathway diagram provides access to a tool to customize diagram colouring and to an ‘About …’ pop-up that briefly describes pathway diagram features and contains a link to the detailed users’ guide. (This guide is also accessible via the ‘documentation’ drop-down menu at the top of the home page).CC BY · PubMed Central
Figure 4. Analysis tool user data submission interface, showing time-series data. Each row represents data for a different gene. Columns contain an identifier (probe set, gene name, etc.) on the left and expression values for four time points to the right, entered as tab-delimited text. UniProt identifiers, gene names and Affimetrix identifiers, among others, can be submitted. The ‘project to human’ box at the bottom of the form, which is selected by default, causes any non-human identifiers in the data to be replaced by their human equivalents and the latter to be used for the analysis. Instructions for formatting data and lists of acceptable identifiers are provided in the users’ guide (Figure 3).
Figure 4. Analysis tool user data submission interface, showing time-series data. Each row represents data for a different gene. Columns contain an identifier (probe set, gene name, etc.) on the left and expression values for four time points to the right, entered as tab-delimited text. UniProt identifiers, gene names and Affimetrix identifiers, among others, can be submitted. The ‘project to human’ box at the bottom of the form, which is selected by default, causes any non-human identifiers in the data to be replaced by their human equivalents and the latter to be used for the analysis. Instructions for formatting data and lists of acceptable identifiers are provided in the users’ guide (Figure 3).CC BY · PubMed Central
Figure 5. Analysis results. Top panels, an analysis of a PRIDE dataset (assay 27 929—http://www.ebi.ac.uk/pride/ws/archive/protein/list/assay/27929.acc in project PXD000072—http://www.ebi.ac.uk/pride/archive/projects/PXD000072) to identify proteins over-expressed in activated human platelet releasate (5). Bottom panels, an expression analysis. Left panels show overlays on the pathways overview; right panels are an overlay of the data for a selected pathway on the pathway diagram. The details panel at the bottom lists results and statistics for each pathway, including numbers of identifiers in the submitted dataset that did not match anything in the Reactome dataset. A binomial test is used to calculate the probability shown for each result, and the P-values are corrected for the multiple testing (Benjamini–Hochberg procedure) that arises from evaluating the submitted list of identifiers against every pathway.
Figure 5. Analysis results. Top panels, an analysis of a PRIDE dataset (assay 27 929—http://www.ebi.ac.uk/pride/ws/archive/protein/list/assay/27929.acc in project PXD000072—http://www.ebi.ac.uk/pride/archive/projects/PXD000072) to identify proteins over-expressed in activated human platelet releasate (5). Bottom panels, an expression analysis. Left panels show overlays on the pathways overview; right panels are an overlay of the data for a selected pathway on the pathway diagram. The details panel at the bottom lists results and statistics for each pathway, including numbers of identifiers in the submitted dataset that did not match anything in the Reactome dataset. A binomial test is used to calculate the probability shown for each result, and the P-values are corrected for the multiple testing (Benjamini–Hochberg procedure) that arises from evaluating the submitted list of identifiers against every pathway.CC BY · PubMed Central
Figure 6. Redesigned search interface, showing term auto suggestion, grouping of results and highlighting of search terms in the results. The check boxes along the left side of the results page allow results to be further limited by species, data type, subcellular location and other parameters.
Figure 6. Redesigned search interface, showing term auto suggestion, grouping of results and highlighting of search terms in the results. The check boxes along the left side of the results page allow results to be further limited by species, data type, subcellular location and other parameters.CC BY · PubMed Central

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Research works printed but not linked: 4

  1. Croft, 2014, The Reactome Pathway Knowledgebase, Nucleic Acids Res., 4, D472, 10.1093/nar/gkt1102 · DOI · Paper page
  2. 10.1093/nar/gku1011 · DOI
  3. 10.1093/nar/gku1179 · DOI · Paper page
  4. 10.1161/ATVBAHA.113.301147 · DOI

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Metadata

Authors
Fabregat, A., Sidiropoulos, K., Garapati, P., Gillespie, M., Hausmann, K., Haw, R., Jassal, B., Jupe, S., Korninger, F., McKay, S., Matthews, L., May, B., Milacic, M., Rothfels, K., Shamovsky, V., Webber, M., Weiser, J., Williams, M., Wu, G., Stein, L., Hermjakob, H., & D'Eustachio, P.
Affiliations
  • European Bioinformatics Institute (GB)
  • Ontario Institute for Cancer Research (CA)
  • New York University (US)
ORCID
Venue
Nucleic Acids Research
Publisher
Oxford University Press (OUP)
Published
2015-12-09
Volume
44
Issue
D1
Pages
D481-D487
ISSN
  • 0305-1048 (ISSN-L)
  • 1362-4962
DOI
10.1093/nar/gkv1351
PMC
PMC4702931
OpenAlex
W1989277387
Cited by
5,605
References
6
Citations by year
2026: 18 · 2025: 133 · 2024: 368 · 2023: 491 · 2022: 738 · 2021: 968 · 2020: 827 · 2019: 667 · 2018: 483 · 2017: 386 · 2016: 265 · 2015: 187
FWCI
153.21
Type
journal article
Language
en
Open access
Licence
Locations
  • Nucleic Acids Research (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Cold Spring Harbor Laboratory Institutional Repository (Cold Spring Harbor Laboratory) (acceptedVersion)
  • HighWire Press Open Archive (submittedVersion)
Funders
  • National Institutes of Health
  • National Human Genome Research Institute (U41HG003751, P41HG003751)
  • National Institute of General Medical Sciences (U54GM114833)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
  • Health Sciences › Medicine › Health Informatics › Biomedical Text Mining and Ontologies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
Keywords
Reactome, signal transduction, metabolic maps, cardiovascular disease, disease annotation, gene expression profiles, somatic mutations
MeSH terms
Humans, Proteins, Software, Signal Transduction, Gene Expression, Knowledge Bases, Metabolic Networks and Pathways, Databases, Chemical

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