Reactome

<h2 id="database-organization">Database organization</h2>
<p>Reactome database releases occur quarterly. 
</p><p>In Reactome, human biological processes are annotated by breaking them down into series of molecular events. Like classical chemistry reactions each Reactome event has input physical entities (substrates) which interact, possibly facilitated by enzymes or other molecular catalysts, to generate output physical entities (products).
</p><p>Reactions include the classical chemical interconversions of intermediary metabolism, binding events, complex formation, transport events that direct molecules between cellular compartments, and events such as the activation of a protein by cleavage of one or more of its peptide bonds. Individual events can be grouped together into pathways.
</p><p>Physical entities can be small molecules like glucose or ATP, or large molecules like DNA, RNA, and proteins, encoded directly or indirectly in the human genome. Physical entities are cross-referenced to relevant external databases, such as <a href="/facts/UniProt/lfDDHjAl">UniProt</a> for proteins and <a href="/facts/ChEBI/zQLG1mbE">ChEBI</a> for small molecules. Localization of molecules to subcellular compartments is a key feature of the regulation of human biological processes, so molecules in the Reactome database are associated with specific locations. Thus in Reactome instances of the same chemical entity in different locations (e.g., extracellular glucose and cytosolic glucose) are treated as distinct chemical entities.
</p><p>The <a href="/facts/Gene_Ontology/Grmg6Q8k">Gene Ontology</a> controlled vocabularies are used to describe the subcellular locations of molecules and reactions, molecular functions, and the larger biological processes that a specific reaction is part of.
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<h2 id="database-content">Database content</h2>
<p>The database contains curated annotations that cover a diverse set of topics in <a href="/facts/Molecular_biology/YgqU35ub">molecular</a> and <a href="/facts/Cellular_biology/kdIBGHub">cellular biology</a>.
</p><p>Reactome invites biological experts as reviewers for completed pathways that are ready for external review. Reviewers will be credited with authorship or reviewership for contributions. Each pathway is associated with a DOI and can be cited as a publication. Reactome contributions in can be easily claimed using the ORCID claiming feature. 
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<h2 id="tools">Tools</h2>
<p>There are tools on the website for viewing an interactive pathway diagram, performing pathway mapping and pathway over-representation analysis and for overlaying expression data onto Reactome pathways. The pathway mapping and over-representation tools take a single column of protein/compound identifiers, Uniprot and ChEBI accessions are preferred but the interface will accept and interpret many other identifiers or symbols. Mixed identifiers can be used.  Over-representation results are presented as a list of statistically over-represented pathways.
</p><p>Expression data is submitted in a multi-column format, the first column identifying the protein, additional columns are expected to be numeric expression values, they can in fact be any numeric value, e.g. differential expression, quantitative proteomics, GWAS scores. The expression data is represented as colouring of the corresponding proteins in pathway diagrams, using the colours of the visible spectrum so 'hot' red colours represent high values. If multiple columns of numeric data are submitted the overlay tool can display them as separate 'experiments', e.g. timepoints or a disease progression.
</p><p>The database can be browsed and searched as an on-line textbook.<a class="footnote-ref" id="fnref:4" href="#fn:4"><sup>4</sup></a> 
</p><p>Reactome also has a ReactomeGSA<a class="footnote-ref" id="fnref:5" href="#fn:5"><sup>5</sup></a> tool, integrated into the Reactome Analysis Tools that allows comparative pathway analyses of multi-omics datasets, with compatibility with single-cell RNA-seq data. Public data from EBI Expression Atlas, Single Cell Expression Atlas, and NCBI GREIN GEO data can be integrated into the analysis. 
</p><p>ReactomeFIViz is a Cytoscape app designed to find pathways and network patterns related to diseases. The app accesses Reactome pathways, perform pathway enrichment analysis for a set of genes, visualize hit pathways, and investigate functional relationships among genes in hit pathways. The app also accesses the Reactome Functional Interaction (FI) network.<a class="footnote-ref" id="fnref:6" href="#fn:6"><sup>6</sup></a> 
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<h3>Related resources</h3>
<p>Other molecular pathway databases
</p>
<ul><li><a href="http://www.genenetwork.org">GeneNetwork</a></li>
<li><a href="http://www.pantherdb.org/pathway/">Panther Pathways</a></li>
<li><a href="/facts/Pathway_commons/2oNyTYJ1">Pathway Commons</a></li>
<li><a href="/facts/KEGG/pK5La8ad">KEGG</a> (The Kyoto Encyclopedia of Genes and Genomes)</li>
<li><a href="/facts/BioCyc_database_collection/Kv8DYYno">BioCyc database collection</a></li>
<li><a href="/facts/BRENDA/SQwz2IDm">BRENDA</a> (The BRaunschweig ENzyme DAtabase)</li>
<li><a href="/facts/WikiPathways/eHNMwWkG">WikiPathways</a> (which exposes Reactome pathways<a class="footnote-ref" id="fnref:7" href="#fn:7"><sup>7</sup></a>)</li>
<li><a href="/facts/Comparative_Toxicogenomics_Database/l8gxneBr">Comparative Toxicogenomics Database</a></li></ul>

<h2 id="references">References</h2>

<ol>
<li id="fn:1"><p>Croft, D.; O'Kelly, G.; Wu, G.; Haw, R.; Gillespie, M.; Matthews, L.; Caudy, M.; Garapati, P.; Gopinath, G.; Jassal, B.; Jupe, S.; Kalatskaya, I.; Mahajan, S.; May, B.; Ndegwa, N.; Schmidt, E.; Shamovsky, V.; Yung, C.; Birney, E.; Hermjakob, H.; d'Eustachio, P.; Stein, L. (2010). "Reactome: A database of reactions, pathways and biological processes". Nucleic Acids Research. 39 (Database issue): D691 – D697. doi:10.1093/nar/gkq1018. PMC 3013646. PMID 21067998. <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3013646" target="_blank">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3013646</a> <a href="#fnref:1" class="footnote-back-ref">↩</a></p></li>
<li id="fn:2"><p>Joshi-Tope, G.; Gillespie, M.; Vastrik, I.; d'Eustachio, P.; Schmidt, E.; De Bono, B.; Jassal, B.; Gopinath, G.; Wu, G.; Matthews, L.; Lewis, S.; Birney, E.; Stein, L. (2004). "Reactome: A knowledgebase of biological pathways". Nucleic Acids Research. 33 (Database issue): D428 – D432. doi:10.1093/nar/gki072. PMC 540026. PMID 15608231. <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC540026" target="_blank">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC540026</a> <a href="#fnref:2" class="footnote-back-ref">↩</a></p></li>
<li id="fn:3"><p>Croft D, Mundo AF, Haw R, Milacic M, Weiser J, Wu G, Caudy M, Garapati P, Gillespie M, Kamdar MR, Jassal B, Jupe S, Matthews L, May B, Palatnik S, Rothfels K, Shamovsky V, Song H, Williams M, Birney E, Hermjakob H, Stein L, D'Eustachio P (2014). "The Reactome pathway knowledgebase". Nucleic Acids Res. 42 (Database issue): D472–7. doi:10.1093/nar/gkt1102. PMC 3965010. PMID 24243840. <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3965010" target="_blank">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3965010</a> <a href="#fnref:3" class="footnote-back-ref">↩</a></p></li>
<li id="fn:4"><p>Haw, R; Stein, L (Jun 2012). "Using the reactome database". Current Protocols in Bioinformatics. Chapter 8: 8.7.1–8.7.23. doi:10.1002/0471250953.bi0807s38. PMC 3427849. PMID 22700314. <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3427849" target="_blank">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3427849</a> <a href="#fnref:4" class="footnote-back-ref">↩</a></p></li>
<li id="fn:5"><p>Griss, Johannes; Viteri, Guilherme; Sidiropoulos, Konstantinos; Nguyen, Vy; Fabregat, Antonio; Hermjakob, Henning (December 2020). "ReactomeGSA - Efficient Multi-Omics Comparative Pathway Analysis". Molecular & Cellular Proteomics. 19 (12): 2115–2125. doi:10.1074/mcp.TIR120.002155. PMC 7710148. PMID 32907876. <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7710148" target="_blank">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7710148</a> <a href="#fnref:5" class="footnote-back-ref">↩</a></p></li>
<li id="fn:6"><p>Wu, Guanming; Feng, Xin; Stein, Lincoln (2010). "A human functional protein interaction network and its application to cancer data analysis". Genome Biology. 11 (5): R53. doi:10.1186/gb-2010-11-5-r53. ISSN 1474-760X. PMC 2898064. PMID 20482850. <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2898064" target="_blank">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2898064</a> <a href="#fnref:6" class="footnote-back-ref">↩</a></p></li>
<li id="fn:7"><p>Bohler, Anwesha; Wu, Guanming; Kutmon, Martina; Pradhana, Leontius Adhika; Coort, Susan L.; Hanspers, Kristina; Haw, Robin; Pico, Alexander R.; Evelo, Chris T.; Blackwell, Kim T. (20 May 2016). "Reactome from a WikiPathways Perspective". PLOS Computational Biology. 12 (5): e1004941. Bibcode:2016PLSCB..12E4941B. doi:10.1371/journal.pcbi.1004941. PMC 4874630. PMID 27203685. <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4874630" target="_blank">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4874630</a> <a href="#fnref:7" class="footnote-back-ref">↩</a></p></li>
</ol>

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Reactome