Identification of potential diagnostic biomarkers of atherosclerosis based on bioinformatics strategy.

ABSTRACT:

Background

Atherosclerosis is the main pathological change in atherosclerotic cardiovascular disease, and its underlying mechanisms are not well understood. The aim of this study was to explore the hub genes involved in atherosclerosis and their potential mechanisms through bioinformatics analysis.

Methods

Three microarray datasets from Gene Expression Omnibus (GEO) identified robust differentially expressed genes (DEGs) by robust rank aggregation (RRA). We performed connectivity map (CMap) analysis and functional enrichment analysis on robust DEGs and constructed a protein‒protein interaction (PPI) network using the STRING database to identify the hub gene using 12 algorithms of cytoHubba in Cytoscape. Receiver operating characteristic (ROC) analysis was used to assess the

SUBMITTER: Zheng Z 

PROVIDER: S-EPMC10176947 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature