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. 2021 May 26;11:11049. doi: 10.1038/s41598-021-90296-2

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© The Author(s) 2021

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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The COVID-19 supergraph integrates drug-target information to form the COVID-19 PHARMACOME. (a) An aggregate of 10 constituent COVID-19 computable models covering a wide spectrum of pathophysiological mechanisms associated with SARS-CoV-2 infection or harmonized to generate the mechanism-based COVID-19 supergraph. (b) The COVID-19 supergraph is annotated with drug-target information from a variety of curated sources to generate the COVID-19 PHARMACOME composed of 150,662 nodes (representing proteins, pathologies, and other biological entities/concepts) and 573,929 edges (indicating relationships or interactions between the pair of nodes they connect).