The mechanistic functional landscape of retinitis pigmentosa: a machine learning-driven approach to therapeutic target discovery.

ABSTRACT:

Background

Retinitis pigmentosa is the prevailing genetic cause of blindness in developed nations with no effective treatments. In the pursuit of unraveling the intricate dynamics underlying this complex disease, mechanistic models emerge as a tool of proven efficiency rooted in systems biology, to elucidate the interplay between RP genes and their mechanisms. The integration of mechanistic models and drug-target interactions under the umbrella of machine learning methodologies provides a multifaceted approach that can boost the discovery of novel therapeutic targets, facilitating further drug repurposing in RP.

Methods

By mapping Retinitis Pigmentosa-related genes (obtained from Orphanet, OMIM and HPO databases) onto KEGG signaling pathways, a collection of signaling functi

SUBMITTER: Esteban-Medina M 

PROVIDER: S-EPMC10848380 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature