RNA is one of the three major biological macromolecules that are essential for all known forms of life. The folding of RNAs into specific tertiary structures is necessary for performing specific functions and their application in drug design.
Due to the high cost of laboratory methods and their time-consuming, it is tried to solve them using computational methods. Due to the NP-hard of this problem, solving it requires heuristic algorithms.
In this seminar, a new method of deep learning is proposed to design RNA using a tertiary structure with sequence length more than 50.