Immune-associated pivotal biomarkers identification and competing endogenous RNA network construction in post-operative atrial fibrillation by comprehensive bioinformatics and machine learning strategies.

ABSTRACT:

Background

Atrial fibrillation (AF) is the most common arrhythmia. Previous studies mainly focused on identifying potential diagnostic biomarkers and treatment strategies for AF, while few studies concentrated on post-operative AF (POAF), particularly using bioinformatics analysis and machine learning algorithms. Therefore, our study aimed to identify immune-associated genes and provide the competing endogenous RNA (ceRNA) network for POAF.

Methods

Three GSE datasets were downloaded from the GEO database, and we used a variety of bioinformatics strategies and machine learning algorithms to discover candidate hub genes. These techniques included identifying differentially expressed genes (DEGs) and circRNAs (DECs), building protein-protein interaction networks, selecting comm

SUBMITTER: Zhou Y 

PROVIDER: S-EPMC9630466 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature