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Updated: Mar 28, 2026

Author Spotlight: Advancing the Analysis of Plasma Extracellular Vesicle Proteome for Cardiovascular Biomarker Studies
Published on: January 31, 2025
Protocol to identify biomarkers in patients with post-COVID condition using multi-omics and machine learning analysis
Mobin Khoramjoo1, Karthik Srinivasan2, Kaiming Wang3
1Department of Physiology, University of Alberta, Edmonton, AB T6G 2H7, Canada; Mazankowski Alberta Heart Institute, University of Alberta, Edmonton, AB T6G 2S2, Canada.
Abstract:
Here, we present a workflow for analyzing multi-omics data of plasma samples in patients with post-COVID condition (PCC). Applicable to various diseases, we outline steps for data preprocessing and integrating diverse assay datasets. Then, we detail statistical analysis to unveil plasma profile changes and identify biomarker-clinical variable associations. The last two steps discuss machine learning techniques for unsupervised clustering of patients based on their inherent molecular similarities and feature selection to identify predictive biomarkers. For complete details on the use and execution of this protocol, please refer to Wang et al.1.

