Using the Reactome Database

Karen Rothfels(Ontario Institute for Cancer Research), M Orlic-Milacic(Ontario Institute for Cancer Research), Lisa Matthews(NYU Langone Health), Robin Haw(Ontario Institute for Cancer Research), Cristoffer Sevilla(European Bioinformatics Institute), Marc Gillespie(Ontario Institute for Cancer Research), Ralf Stephan(Ontario Institute for Cancer Research), Chuqiao Gong(European Bioinformatics Institute), Eliot Ragueneau(European Bioinformatics Institute), Bruce May(Ontario Institute for Cancer Research), Veronica Shamovsky(NYU Langone Health), A. Jordan Wright(Ontario Institute for Cancer Research), Joel Weiser(Ontario Institute for Cancer Research), Deidre Beavers(Oregon Health & Science University), Patrick Conley(Oregon Health & Science University), Krishna Kumar Tiwari(European Bioinformatics Institute), Bijay Jassal(Ontario Institute for Cancer Research), Johannes Griss(European Bioinformatics Institute), Andrea Senff‐Ribeiro(Ontario Institute for Cancer Research), Timothy Brunson(Oregon Health & Science University), Robert Petryszak(European Bioinformatics Institute), Henning Hermjakob(European Bioinformatics Institute), Peter D’Eustachio(NYU Langone Health), Guanming Wu(Oregon Health & Science University), Lincoln Stein(Ontario Institute for Cancer Research)
Current Protocols
April 1, 2023
Cited by 56Open Access
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Abstract

Pathway databases provide descriptions of the roles of proteins, nucleic acids, lipids, carbohydrates, and other molecular entities within their biological cellular contexts. Pathway-centric views of these roles may allow for the discovery of unexpected functional relationships in data such as gene expression profiles and somatic mutation catalogues from tumor cells. For this reason, there is a high demand for high-quality pathway databases and their associated tools. The Reactome project (a collaboration between the Ontario Institute for Cancer Research, New York University Langone Health, the European Bioinformatics Institute, and Oregon Health & Science University) is one such pathway database. Reactome collects detailed information on biological pathways and processes in humans from the primary literature. Reactome content is manually curated, expert-authored, and peer-reviewed and spans the gamut from simple intermediate metabolism to signaling pathways and complex cellular events. This information is supplemented with likely orthologous molecular reactions in mouse, rat, zebrafish, worm, and other model organisms. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Browsing a Reactome pathway Basic Protocol 2: Exploring Reactome annotations of disease and drugs Basic Protocol 3: Finding the pathways involving a gene or protein Alternate Protocol 1: Finding the pathways involving a gene or protein using UniProtKB (SwissProt), Ensembl, or Entrez gene identifier Alternate Protocol 2: Using advanced search Basic Protocol 4: Using the Reactome pathway analysis tool to identify statistically overrepresented pathways Basic Protocol 5: Using the Reactome pathway analysis tool to overlay expression data onto Reactome pathway diagrams Basic Protocol 6: Comparing inferred model organism and human pathways using the Species Comparison tool Basic Protocol 7: Comparing tissue-specific expression using the Tissue Distribution tool.


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