The reactome pathway knowledgebase 2022

• Published in: Nucleic acids research Vol. 50; no. D1; pp. D687 - D692
• Main Authors: Gillespie, Marc, Jassal, Bijay, Stephan, Ralf, Milacic, Marija, Rothfels, Karen, Senff-Ribeiro, Andrea, Griss, Johannes, Sevilla, Cristoffer, Matthews, Lisa, Gong, Chuqiao, Deng, Chuan, Varusai, Thawfeek, Ragueneau, Eliot, Haider, Yusra, May, Bruce, Shamovsky, Veronica, Weiser, Joel, Brunson, Timothy, Sanati, Nasim, Beckman, Liam, Shao, Xiang, Fabregat, Antonio, Sidiropoulos, Konstantinos, Murillo, Julieth, Viteri, Guilherme, Cook, Justin, Shorser, Solomon, Bader, Gary, Demir, Emek, Sander, Chris, Haw, Robin, Wu, Guanming, Stein, Lincoln, Hermjakob, Henning, D’Eustachio, Peter
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 07-01-2022
• Subjects: Antiviral Agents - pharmacology; COVID-19 - metabolism; Data Curation; Database Issue; Genome, Human; Host-Pathogen Interactions; Humans; Knowledge Bases; Proteins - genetics; Proteins - metabolism; Signal Transduction; Software
• ISSN: 0305-1048; 1362-4962
• DOI: 10.1093/nar/gkab1028

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.