Identification of biomarkers associated with diagnosis of acute lung injury based on bioinformatics and machine learning.

ABSTRACT:

Background

Acute lung injury (ALI) is an acute inflammatory disease characterized by excess production of inflammatory factors in lung tissue and has a high mortality. This research was designed for the identification of novel diagnostic biomarkers for ALI and analyzing the possible association between critical genes and infiltrated immune cells.

Methods

The study used 2 datasets (GSE2411 and GSE18341) to identify differentially expressed genes (DEGs) between 2 groups. Then we performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses to identify the functions of these DEGs. The study also used SVM-recursive feature elimination analysis and least absolute shrinkage and selection operator regression model to screen possible markers. The study further analyze

SUBMITTER: Jing H 

PROVIDER: S-EPMC10443773 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature