Identification of methylation signatures and rules for predicting the severity of SARS-CoV-2 infection with machine learning methods.

ABSTRACT: Patients infected with SARS-CoV-2 at various severities have different clinical manifestations and treatments. Mild or moderate patients usually recover with conventional medical treatment, but severe patients require prompt professional treatment. Thus, stratifying infected patients for targeted treatment is meaningful. A computational workflow was designed in this study to identify key blood methylation features and rules that can distinguish the severity of SARS-CoV-2 infection. First, the methylation features in the expression profile were deeply analyzed by a Monte Carlo feature selection method. A feature list was generated. Next, this ranked feature list was fed into the incremental feature selection method to determine the optimal features for different classification algorithms, t

SUBMITTER: Liu Z 

PROVIDER: S-EPMC9537378 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature