Parkinson's Disease Gene Biomarkers Screened by the LASSO and SVM Algorithms.

ABSTRACT: Parkinson's disease (PD) is a common progressive neurodegenerative disorder. Various evidence has revealed the possible penetration of peripheral immune cells in the substantia nigra, which may be essential for PD. Our study uses machine learning (ML) to screen for potential PD genetic biomarkers. Gene expression profiles were screened from the Gene Expression Omnibus (GEO). Differential expression genes (DEGs) were selected for the enrichment analysis. A protein-protein interaction (PPI) network was built with the STRING database (Search Tool for the Retrieval of Interacting Genes), and two ML approaches, namely least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE), were employed to identify candidate genes. The external

SUBMITTER: Bao Y 

PROVIDER: S-EPMC9953979 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature