2026-10-16T08:55:05Z https://data.mendeley.com/oai

oai:data.mendeley.com/sv8hx7gkxp.1 2022-11-18T22:08:09Z

Gerner, Christopher A multi-omics based anti-inflammatory immune signature characterizes Long COVID Syndrome - Kovarik et al. Mendeley Data Supplementary Table S1 related to Figure 1: Student's t-test statistics between long-covid and recovered, long-covid and healthy as well as recovered and healthy are shown. For each identified protein, log2 label-free quantification (LFQ) intensities, numbers of identified peptides, numbers of identified unique peptides as well as the sequence coverage is listed. Supplementary Table S2 related to Figure 2: Student's t-test statistics between long-covid and recovered, long-covid and healthy as well as recovered and healthy are shown. For each identified eicosanoid normalized area under the curve (nAUC) values are listed. Supplementary Table S3 related to Figure 3: Student's t-test statistics between long-covid and recovered, long-covid and healthy as well as recovered and healthy are shown. For each identified metabolite log2 concentrations in µM are listed. Supplementary Table S4 related to Figure 3: Heatmap data matrix. Normalized values generated by dividing the concentration of each lipid through the average concentration of this lipid over all samples. Proteomics Metabolomics Eicosanoids Dataset doi:10.17632/sv8hx7gkxp.1 oai:data.mendeley.com/sv8hx7gkxp.1 Creative Commons Attribution 4.0 International http://creativecommons.org/licenses/by/4.0 https://data.mendeley.com/datasets/sv8hx7gkxp 2022-11-18T22:08:09Z