Identification of miRNA biomarkers for essential hypertension in small samples based on MPGAM.

ABSTRACT: Essential hypertension (EH) is one of the most widespread chronic diseases globally, with a multifactorial etiology. MicroRNAs (miRNAs) are key regulators in the development and progression of EH and hold great promise as biomarkers. However, reliably identifying EH-related miRNA biomarkers in small-sample datasets remains challenging. To address these limitations, we propose a novel computational framework, the Modular Probability-driven Global Analytical Method (MPGAM), tailored for biomarker discovery in small-sample settings. MPGAM integrates three key innovations: (1) the Dual-Index Nearest Neighbor Similarity Measure (DINNSM), which captures local similarity structures more accurately than conventional correlation-based methods; (2) a multi-dimensional module evaluation strategy that

SUBMITTER: Li Z 

PROVIDER: S-EPMC12559234 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature