MixOmics Integration of Biological Datasets Identifies Highly Correlated Variables of COVID-19 Severity.

ABSTRACT: Despite several years passing since the COVID-19 pandemic was declared, challenges remain in understanding the factors that can predict the severity of COVID-19 disease and complications of SARS-CoV-2 infection. While many large-scale multi-omic datasets have been published, integration of these datasets has the potential to substantially increase the biological insight gained, allowing a more complex comprehension of the disease pathogenesis. Such insight may improve our ability to predict disease progression, detect severe cases more rapidly and develop effective therapeutics. In this study, we have applied an innovative machine learning algorithm to delineate COVID severity based on the integration of paired samples of proteomic and transcriptomic data from a small cohort of patients te

SUBMITTER: Harriott NC 

PROVIDER: S-EPMC12111767 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature