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Nucleic Acids Res. 2020 Jan 8;48(D1):D498-D503. doi: 10.1093/nar/gkz1031.

The reactome pathway knowledgebase.

Author information

1
Ontario Institute for Cancer Research, Toronto, ON M5G0A3, Canada.
2
NYU School of Medicine, New York, NY 10016, USA.
3
European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK.
4
Open Targets, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK.
5
College of Pharmacy and Health Sciences, St. John's University, Queens, NY 11439, USA.
6
Oregon Health and Science University, Portland, OR 97239, USA.
7
Department of Molecular Genetics, University of Toronto, Toronto, ON, M5S 1A1, Canada.
8
National Center for Protein Sciences, Beijing, China.

Abstract

The Reactome Knowledgebase (https://reactome.org) provides molecular details of signal transduction, transport, DNA replication, metabolism and other cellular processes as an ordered network of molecular transformations in a single consistent data model, an extended version of a classic metabolic map. Reactome functions both as an archive of biological processes and as a tool for discovering functional relationships in data such as gene expression profiles or somatic mutation catalogs from tumor cells. To extend our ability to annotate human disease processes, we have implemented a new drug class and have used it initially to annotate drugs relevant to cardiovascular disease. Our annotation model depends on external domain experts to identify new areas for annotation and to review new content. New web pages facilitate recruitment of community experts and allow those who have contributed to Reactome to identify their contributions and link them to their ORCID records. To improve visualization of our content, we have implemented a new tool to automatically lay out the components of individual reactions with multiple options for downloading the reaction diagrams and associated data, and a new display of our event hierarchy that will facilitate visual interpretation of pathway analysis results.

PMID:
31691815
DOI:
10.1093/nar/gkz1031

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