Abstract
Genetic diseases, caused by mutations in genes, continue to represent a major global health challenge. Data-driven approaches, particularly those involving high-throughput genomic sequencing, machine learning, and computational modeling, have revolutionized our understanding of genetic diseases. This article explores the role of data-driven approaches in identifying genetic variants associated with disease, understanding disease mechanisms, and developing potential therapeutic strategies. We also discuss the integration of genomic, clinical, and environmental data in personalized medicine, and highlight challenges and future directions in the study of genetic diseases.
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