ARTIFICIAL INTELLIGENCE IN GENETICS AND MOLECULAR BIOLOGY RESEARCH

Abstract

In the field of genetics and molecular biology, Artificial Intelligence (AI) has become a game-changer, facilitating the swift interpretation of intricate genetic data and enhancing the precision of genomic studies. High-throughput sequencing methods have led to a tremendous amount of data and sophisticated computational approaches are needed to interpret these data effectively. AI applications such as machine learning, deep learning, and neural networks can aid in gene prediction, protein structure analysis, disease diagnosis, discovery of biomarkers, drug development, and precision medicine. The study involved a secondary research approach which was conducted by surveying the latest published scientific literature in the field of genetics and molecular biology, and AI. The results demonstrate the potential for AI to markedly increase the accuracy of predictions, minimize research time and aid in decision-making for biological investigations. But issues of data quality, the transparency of the algorithms, ethical and moral considerations, and computational complexity are all relevant. The study concludes that AI has emerged as a crucial asset in the field of genetics and molecular biology research, highlighting the need for responsible implementation and collaboration between various disciplines.