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. 2022 Dec 28;12:22471. doi: 10.1038/s41598-022-26965-7

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© The Author(s) 2022

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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Topological data analysis (TDA) network of protein expression during the middle-phase of COVID-19. Distinct protein expression phenotypes (Clusters 1, 2, and 3) were identified based on density and break points in the network and persistence of the clusters. Each node represents a combination of 12 plasma protein analyte levels and its size increases with the number of participants that are included. Edges (lines between nodes) indicate that patients are represented in more than one node. The network is colored by the average score on the disease severity scale (from outpatients without limitations [green] to death [red]) in each node. Analysis was performed on the EurekaAI Workbench (SymphonyAI, Los Altos, CA, USA).