(untitled) (International Journal of Latest Technology in Engineering Management & Applied Science, 2025)
Abstract: "Artificial Intelligence (AI) has emerged as a transformative instrument in biological sciences, facilitating the analysis of complex biological datasets, predicting molecular interactions, and automating laboratory and field operations.". This paper explores key AI strategies—machine learning, deep learning, computer vision, and natural language processing (NLP)—and their applications across genomics, proteomics, taxonomy, ecology, and medical diagnostics. Recent advancements in artificial intelligence include the utilization of models such as convolutional neural networks (CNNs) and support vector machines (SVMs). The integration of AI with biological databases accelerates drug discovery, species classification, and environmental assessment. The study highlights future directions and ethical considerations in implementing AI responsibly for sustainable biological research.