Role of Advanced Artificial Intelligence Techniques in Bioinformatics

Abstract

In bioinformatics science and computational molecular biology, artificial intelligence (AI) has gained researchers’ interest. It has become common for scientists to use off-the-shelf systems to identify and mine their AI algorithms of various forms. Researchers face difficulties in finding the right approach, with numerous intelligent approaches accessible in the literature that may be used for a particular collection of data. This chapter illuminates the close connections between AI and bioinformatics established for many years. AI techniques such as machine learning (ML) and deep learning (DL) have shown explosive growth in their application to bioinformatics. AI has demonstrated thrillingly good power to mine the complicated relationships hidden in large-scale biological and biomedical data. For both bioinformatics and computer sciences, significant advances have been made over the years, leading to many breakthroughs in the respective fields. As bioinformatics, innovative approaches to interpreting the vast data continue to be sought with meaningful results. AI and its techniques will be used to analyze information in less time and to identify the vast biological data volume. Numerous AI algorithms in bioinformatics research have been developed and implemented. These algorithms are used to produce knowledge effectively. Algorithms are focused on AI applications to explore disease vaccinations, molecular docking tests, novel products, machines, and tools in molecular dynamic simulations.