The reactome pathway knowledgebase 2022

Marc Gillespie(Ontario Institute for Cancer Research), Bijay Jassal(Ontario Institute for Cancer Research), Ralf Stephan(Ontario Institute for Cancer Research), M Orlic-Milacic(Ontario Institute for Cancer Research), Karen Rothfels(Ontario Institute for Cancer Research), Andrea Senff‐Ribeiro(Ontario Institute for Cancer Research), Johannes Griss(European Bioinformatics Institute), Cristoffer Sevilla(European Bioinformatics Institute), Lisa Matthews(New York University), Chuqiao Gong(European Bioinformatics Institute), Chuan Deng(Chongqing University of Posts and Telecommunications), Thawfeek Varusai(European Bioinformatics Institute), Eliot Ragueneau(European Bioinformatics Institute), Yusra Haider(European Bioinformatics Institute), Bruce May(Ontario Institute for Cancer Research), Veronica Shamovsky(New York University), Joel Weiser(Ontario Institute for Cancer Research), Timothy Brunson(Oregon Health & Science University), Nasim Sanati(Oregon Health & Science University), Liam Beckman(Oregon Health & Science University), Xiang Shao(Oregon Health & Science University), Antonio Fabregat(European Bioinformatics Institute), Konstantinos Sidiropoulos(European Bioinformatics Institute), Julieth Murillo(Centro Internacional de Entrenamiento e Investigaciones Medicas), Guilherme Viteri(European Bioinformatics Institute), Justin Cook(Ontario Institute for Cancer Research), Solomon I. Shorser(Ontario Institute for Cancer Research), Gary D. Bader(University of Toronto), Emek Demir(Oregon Health & Science University), Chris Sander(Dana-Farber Cancer Institute), Robin Haw(Ontario Institute for Cancer Research), Guanming Wu(Oregon Health & Science University), Lincoln Stein(Ontario Institute for Cancer Research), Henning Hermjakob(European Bioinformatics Institute), Peter D’Eustachio(New York University)
Nucleic Acids Research
October 14, 2021
Cited by 2,527Open Access
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Abstract

The Reactome Knowledgebase (https://reactome.org), an Elixir core resource, provides manually curated molecular details across a broad range of physiological and pathological biological processes in humans, including both hereditary and acquired disease processes. The processes are annotated as an ordered network of molecular transformations in a single consistent data model. Reactome thus functions both as a digital archive of manually curated human biological processes and as a tool for discovering functional relationships in data such as gene expression profiles or somatic mutation catalogs from tumor cells. Recent curation work has expanded our annotations of normal and disease-associated signaling processes and of the drugs that target them, in particular infections caused by the SARS-CoV-1 and SARS-CoV-2 coronaviruses and the host response to infection. New tools support better simultaneous analysis of high-throughput data from multiple sources and the placement of understudied ('dark') proteins from analyzed datasets in the context of Reactome's manually curated pathways.


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