Petrographic and Geochemical Studies of Lateritic soils in Kwara State Polytechnic Ilorin

Artificial intelligence and machine learning developments applied to large biological datasets have significantly changed computational biology. This review methodically summarizes paradigm-shifting approaches that are transforming biological research in the areas of quantum computing, systems-level integration, variant detection, protein structure prediction, and foundation models. We review twenty papers published between 2021 and 2025, demonstrating the importance of computational techniques in deriving useful insights from high dimensional biological data. Data standardization, model transferability, algorithmic interpretability, and computational accessibility are still major issues. Quantum algorithm development, polypharmacology prediction, and rational protein engineering are future priorities. This review illustrates how computational methods radically alter bio logical research paradigms and facilitate the development of precision medicine.