Multi-omic analysis reveals enriched pathways associated with COVID-19 and COVID-19 severity

COVID-19 is a disease characterized by its seemingly unpredictable clinical outcomes. In order to better understand the molecular signature of the disease, a recent multi-omics study was done which looked at correlations between biomolecules and used a tree- based machine learning approach to predic...

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Veröffentlicht in:	PloS one 2022-04, Vol.17 (4), p.e0267047-e0267047
Hauptverfasser:	Lipman, Danika, Safo, Sandra E, Chekouo, Thierry
Format:	Artikel
Sprache:	eng
Schlagworte:	Analysis Biology and Life Sciences Biomolecules Cell cycle Cell death Cholesterol Clinical outcomes Comorbidity Coronaviruses Correlation Correlation analysis COVID-19 Datasets Funding Gene sequencing Hospitals Humans Inflammation Inflammatory response Lipids Machine Learning Medicine and Health Sciences Metabolites Metabolomics Metabolomics - methods Pathways Physical Sciences Principal components analysis Proteins Proteomics Proteomics - methods Quality control Regression analysis Regression models Research and Analysis Methods RNA sequencing Severe acute respiratory syndrome coronavirus 2 Signs and symptoms Stability analysis
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