Reactome
Reactome is a free online database of
Reactome: a database of reactions,
biological pathways.[1][2][3] There are several
Reactomes that concentrate on specific pathways and biological processes.
organisms, the largest of these is focused on
human biology, the following description
concentrates on the human Reactome. It is Content
authored by biologists, in collaboration with
Description Reactome: a database of reactions,
Reactome editorial staff. The content is cross-
pathways and biological processes.
referenced to many bioinformatics databases.
The rationale behind Reactome is to visually Contact
represent biological pathways in full Primary citation PMID 29145629 (https://pubmed.nc
mechanistic detail, while making the source bi.nlm.nih.gov/29145629)
data available in a computationally accessible
format. Access
Data format BioPAX
The website can be used to browse pathways SBML
and submit data to a suite of data analysis
tools. The underlying data is fully Website https://reactome.org
downloadable in a number of standard Download URL https://reactome.org/download-data
formats including PDF, SBML and BioPAX.
Web service URL https://reactome.org/ContentService/
Pathway diagrams use a Systems Biology
Graphical Notation (SBGN)-based style.
The core unit of the Reactome data model is the reaction. Entities (nucleic acids, proteins, complexes and
small molecules) participating in reactions form a network of biological interactions and are grouped into
pathways. Examples of biological pathways in Reactome include signaling, innate and acquired immune
function, transcriptional regulation, translation, apoptosis and classical intermediary metabolism.
The pathways represented in Reactome are species-specific, with each pathway step supported by literature
citations that contain an experimental verification of the process represented. If no experimental verification
using human reagents exists, pathways may contain steps manually inferred from non-human experimental
details, but only if an expert biologist, named as Author of the pathway, and a second biologist, names as
reviewer, agree that this is a valid inference to make. The human pathways are used to computationally
generate by an orthology-based process derived pathways in other organisms.
Database organization
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).
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.
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 UniProt for proteins and ChEBI 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.
The Gene Ontology 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.
Database content
The database contains curated annotations that cover a diverse set of topics in molecular and cellular
biology. Details of current and future annotation projects can be found in the calendar of annotation projects
(http://www.reactome.org/editorial_calendar_public.htm).
Topics of annotation include;
cell cycle
metabolism
signaling
transport
cell motility
immune function
host-virus interaction
neural function
Tools
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.
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.
The database can be browsed and searched as an on-line textbook.[4] An on-line users' guide is available.
Users can also download the current data set or individual pathways and reactions in a variety of formats
including PDF, BioPAX, and SBML[5]
Links to Reactome
Reactome (https://twitter.com/reactome) on Twitter
Reactome Quick Tour on EBI Train OnLine (http://www.ebi.ac.uk/training/online/course/react
ome-quick-tour)
See also
KEGG (The Kyoto Encyclopedia of Genes and Genomes)
BioCyc database collection
BRENDA (The BRaunschweig ENzyme DAtabase)
WikiPathways (which exposes Reactome pathways[6])
Comparative Toxicogenomics Database
References
1. 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" (https://www.ncbi.
nlm.nih.gov/pmc/articles/PMC3013646). Nucleic Acids Research. 39 (Database issue):
D691–D697. doi:10.1093/nar/gkq1018 (https://doi.org/10.1093%2Fnar%2Fgkq1018).
PMC 3013646 (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3013646). PMID 21067998
(https://pubmed.ncbi.nlm.nih.gov/21067998).
2. 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" (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC540
026). Nucleic Acids Research. 33 (Database issue): D428–D432. doi:10.1093/nar/gki072 (ht
tps://doi.org/10.1093%2Fnar%2Fgki072). PMC 540026 (https://www.ncbi.nlm.nih.gov/pmc/ar
ticles/PMC540026). PMID 15608231 (https://pubmed.ncbi.nlm.nih.gov/15608231).
3. 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" (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3965010).
Nucleic Acids Res. 42 (Database issue): D472–7. doi:10.1093/nar/gkt1102 (https://doi.org/1
0.1093%2Fnar%2Fgkt1102). PMC 3965010 (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC
3965010). PMID 24243840 (https://pubmed.ncbi.nlm.nih.gov/24243840).
4. Haw, R; Stein, L (Jun 2012). "Using the reactome database" (https://www.ncbi.nlm.nih.gov/p
mc/articles/PMC3427849). Current Protocols in Bioinformatics. Chapter 8: Unit8.7.
doi:10.1002/0471250953.bi0807s38 (https://doi.org/10.1002%2F0471250953.bi0807s38).
PMC 3427849 (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3427849). PMID 22700314
(https://pubmed.ncbi.nlm.nih.gov/22700314).
5. Croft, D (2013). Building models using Reactome pathways as templates. Methods in
Molecular Biology. Vol. 1021. pp. 273–83. doi:10.1007/978-1-62703-450-0_14 (https://doi.or
g/10.1007%2F978-1-62703-450-0_14). ISBN 978-1-62703-449-4. PMID 23715990 (https://p
ubmed.ncbi.nlm.nih.gov/23715990).
6. 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" (https://www.ncbi.nlm.n
ih.gov/pmc/articles/PMC4874630). PLOS Computational Biology. 12 (5): e1004941.
Bibcode:2016PLSCB..12E4941B (https://ui.adsabs.harvard.edu/abs/2016PLSCB..12E4941
B). doi:10.1371/journal.pcbi.1004941 (https://doi.org/10.1371%2Fjournal.pcbi.1004941).
PMC 4874630 (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4874630). PMID 27203685
(https://pubmed.ncbi.nlm.nih.gov/27203685).
Related resources
Other molecular pathway databases
GeneNetwork (http://www.genenetwork.org)
Panther Pathways (http://www.pantherdb.org/pathway/)
Pathway Commons
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