Selection of key genes for dilated cardiomyopathy based on machine learning algorithms and assessment of diagnostic accuracy.

ABSTRACT:

Background

The mechanisms of the occurrence and progression of dilated cardiomyopathy are still unclear and further exploration is needed. The upgrading of programming languages and the improvement of biological databases have created conditions for us to explore the structural and functional information of biological molecules at the nucleic acid and protein levels, screen key pathogenic genes, and elucidate pathogenic mechanisms. This study aimed to screen key pathogenic genes using machine learning algorithms and explore the correlation between key genes and immune microenvironment through transcriptome sequencing data sets of myocardial samples from patients with dilated cardiomyopathy, providing new ideas for elucidating the pathogenesis of the disease.

Methods

The tran

SUBMITTER: Chen T 

PROVIDER: S-EPMC10482651 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature