THE DIGITAL TRANSFORMATION OF MUSCULAR DYSTROPHY RESEARCH: A REVIEW

Abstract

Muscular dystrophies (MDs) are inherited neuromuscular disorders that cause progressive skeletal muscle weakness, impaired mobility, and significant clinical burden. Although genomic technologies have greatly enhanced variant detection, the wide genetic diversity and overlapping symptoms among MD subtypes still complicate diagnosis and patient management. Bioinformatics now plays a crucial role in advancing MD research by improving variant interpretation, protein structure analysis, and multi-omics integration, while also enabling quantitative imaging and data-driven classification. Persistent challenges such as limited datasets, heterogeneous methodologies, and reduced clinical interpretability slow the translation of computational insights into practice. Strengthening data-sharing strategies and developing more transparent analytical frameworks will help accelerate early diagnosis, personalized care, and therapeutic innovation in muscular dystrophy.