<![CDATA[In recent decades, artificial intelligence (AI) has significantly advanced and shown great potential across various fields, including bioinformatics. This paper examines current trends in AI applications within bioinformatics, highlighting future potentials and the challenges of integrating these technologies. The research utilizes secondary data collection from scientific literature, books, conference reports, and official documents on AI and bioinformatics, sourced from reputable databases like Scopus, IEEE, PubMed, and Google Scholar. Through comparative analysis, similarities, differences, and technological advancements were identified and discussed. Descriptive narrative interpretation was employed to provide a holistic view of AI trends and potential in bioinformatics. Key findings indicate that AI, particularly machine learning and deep learning, is instrumental in genomic data analysis, protein structure prediction, drug discovery, and clinical bioinformatics. Furthermore, the study underscores the benefits of AI in enhancing data analysis accuracy and efficiency, while addressing ethical and technical challenges. Future prospects emphasize the importance of interdisciplinary collaboration to fully leverage AI's capabilities in bioinformatics.]]>
Copyrights © 2025
