A computational framework for identifying cytoskeletal genes associated with age-related diseases.

ABSTRACT: The cytoskeleton comprises polymers from protein filaments shaped in an organized structure. This structure contributes significantly to the cell's function and viability. Decades of research have implicated that the cytoskeleton's dynamic nature is associated with downstream signaling events that further regulate cellular activity and control aging and neurodegeneration. This study aims to investigate the transcriptional changes of the cytoskeletal genes and their regulators in five age-related diseases: Hypertrophic Cardiomyopathy (HCM), Coronary Artery Disease (CAD), Alzheimer's disease (AD), Idiopathic Dilated Cardiomyopathy (IDCM), and Type 2 Diabetes Mellitus (T2DM). An integrative approach of machine learning-based models and differential expression analysis was employed to identify

SUBMITTER: Elghaish RA 

PROVIDER: S-EPMC12033331 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature