The Integration of Machine Learning and Bioinformatics in Disease Prediction

Abstract

Machine learning (ML) and bioinformatics are increasingly integrated to enhance disease prediction and understanding of disease mechanisms. The ability to analyze large-scale biological datasets, such as genomic, transcriptomic, and proteomic data, with advanced machine learning algorithms has revolutionized the way diseases are predicted, diagnosed, and treated. This article explores the integration of ML and bioinformatics in disease prediction, with a focus on genomic data analysis, biomarker discovery, and disease risk assessment. We also discuss the challenges, opportunities, and future directions of this integration in advancing personalized medicine and healthcare.