The Role of Artificial Intelligence (AI) in Genomics

Abstract

Artificial Intelligence (AI) is creating computer systems capable of performing tasks that require human intelligence. Medical AI applications have recently attracted significant attention due to advancements in AI hardware and software, deep learning algorithms, and graphics processing units (GPUs) that enable their training. While other AI subtypes have started to show similar progress in multiple diagnostic modalities, AI-based computer vision methods are poised to transform image-based diagnostics into clinical diagnostics. In specific fields, such as therapeutic genomics, large and complex genetic data are processed using a particular type of AI algorithm called deep learning. Numerous practical applications across a range of industries are being transformed by artificial intelligence (AI). Several conventional machine-learning techniques have been applied in genomics to comprehend the dynamics of genetic data. AI enables rapid identification of genetic variants, determination of gene functions, and the uncovering of intricate genetic relationships by combining machine learning algorithms, deep learning models, and data-driven insights. AI-powered technologies have significantly cut costs and time by streamlining the genome sequencing, annotation, and editing procedures. Additionally, AI supports personalized medicine by evaluating each person's unique genomic profile to forecast illness risks, enhance treatment regimens, and find new therapeutic targets. Additionally, the combination of AI and genomics has accelerated advances in agricultural genomics, drug development, and biological evolution research.

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