Identification of ferroptosis-related genes in type 2 diabetes mellitus based on machine learning.

ABSTRACT:

Background

Type 2 diabetes mellitus (T2DM), which has a high incidence and several harmful consequences, poses a severe danger to human health. Research on the function of ferroptosis in T2DM is increasing. This study uses bioinformatics techniques identify new diagnostic T2DM biomarkers associated with ferroptosis.

Methods

To identify ferroptosis-related genes (FRGs) that are differentially expressed between T2DM patients and healthy individuals, we first obtained T2DM sequencing data and FRGs from the Gene Expression Omnibus (GEO) database and FerrDb database. Then, drug-gene interaction networks and competitive endogenous RNA (ceRNA) networks linked to the marker genes were built after marker genes were filtered by two machine learning algorithms (LASSO and SVM-RFE algori

SUBMITTER: Wang S 

PROVIDER: S-EPMC10566453 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature