Identifying key genes related to inflammasome in severe COVID-19 patients based on a joint model with random forest and artificial neural network.

ABSTRACT:

Background

The coronavirus disease 2019 (COVID-19) has been spreading astonishingly and caused catastrophic losses worldwide. The high mortality of severe COVID-19 patients is an serious problem that needs to be solved urgently. However, the biomarkers and fundamental pathological mechanisms of severe COVID-19 are poorly understood. The aims of this study was to explore key genes related to inflammasome in severe COVID-19 and their potential molecular mechanisms using random forest and artificial neural network modeling.

Methods

Differentially expressed genes (DEGs) in severe COVID-19 were screened from GSE151764 and GSE183533 via comprehensive transcriptome Meta-analysis. Protein-protein interaction (PPI) networks and functional analyses were conducted to identify mo

SUBMITTER: Ou H 

PROVIDER: S-EPMC10126306 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature