ARTIFICIAL INTELLIGENCE (AI) AND MACHINE LEARNING (ML) IN BIOLOGY

Artificial Intelligence (AI) and Machine Learning (ML) are reshaping the field of biology by providing advanced computational tools to manage, analyze, and interpret complex biological data.As biological research generates increasingly large and multidimensional datasets-from genomic sequences and proteomic profiles to highresolution imaging-AI and ML have emerged as essential technologies for identifying patterns, modeling systems, and making predictive inferences.These approaches are revolutionizing traditional methodologies across diverse biological disciplines, including genomics, systems biology, drug discovery, medical diagnostics, and synthetic biology.Through applications such as deep learning-based protein structure prediction, automated image analysis, and personalized medicine algorithms, AI and ML are accelerating scientific discovery, improving accuracy, and reducing the time and cost of experimental research.This paper reviews current advancements, highlights key breakthroughs, and discusses emerging trends and challenges in the integration of AI and ML within the biological sciences.Ultimately, the convergence of computational intelligence and biological understanding is fostering a new era of data-driven discovery and innovation in the life sciences.