Deep Learning in Genomics: Advancements in Predicting Genetic Disorders

Abstract

Deep learning (DL) has significantly advanced the field of genomics, offering powerful tools for predicting genetic disorders. Recent developments in DL models have revolutionized the way we analyze genetic data, enabling more accurate predictions and providing insights into previously unexplored genomic variations. By leveraging large-scale genomic datasets, DL models can identify genetic markers associated with various genetic disorders, improve diagnostic accuracy, and offer potential for personalized medicine. This paper explores the applications of deep learning in genomics, the challenges faced, and the future directions in this transformative field.