A Review on Genomics Data Analysis using Machine Learning

The advancements in genomics research have led to an exponential growth in the amount of data generated from various sequencing technologies. Analyzing this vast amount of genomic data is a complex task that can provide valuable insights into biological processes, disease mechanisms, and personalized medicine. In recent years, machine learning has emerged as a powerful tool for genomic data analysis, enabling researchers to uncover hidden patterns, make predictions, and gain a deeper understanding of the genome. This review aims to provide an overview of the applications of machine learning in genomics data analysis, highlighting its potential, challenges, and future directions.