Abstract
In this review, the author, who specializes in bioinformatics, provides a comprehensive explanation of RNA design, from fundamentals to cutting-edge technologies. The review introduces RNA design methodologies, including RNA inverse folding and mRNA design, based on the relationships between RNA sequence, structure, and function. Furthermore, it details new deep learning-based methods, RaptGen and RfamGen, demonstrating efficient design approaches for RNA aptamer sequences and functional RNA family sequences. The review also discusses future perspectives, including integration with high-throughput experimental technologies, large language models, and applications of quantum computing.
