In Silico Modeling of Fabry Disease Pathophysiology for the Identification of Early Cellular Damage Biomarker Candidates.

ABSTRACT: Fabry disease (FD) is an X-linked lysosomal disease whose ultimate consequences are the accumulation of sphingolipids and subsequent inflammatory events, mainly at the endothelial level. The outcomes include different nervous system manifestations as well as multiple organ damage. Despite the availability of known biomarkers, early detection of FD remains a medical need. This study aimed to develop an in silico model based on machine learning to identify candidate vascular and nervous system proteins for early FD damage detection at the cellular level. A combined systems biology and machine learning approach was carried out considering molecular characteristics of FD to create a computational model of vascular and nervous system disease. A data science strategy was applied to identify risk

SUBMITTER: Gervas-Arruga J 

PROVIDER: S-EPMC11477023 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature