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RNAs play a fundamental role in many biological and medical processes and the activity of RNA is directly dependent to itsstructure. Designing RNA structures is a basic problem in biology that is important in the treatment and nanotechnology. In this regard, some algorithms have been formed to predict RNA secondary structure. In this paper, we present an algorithm to accurately predict RNA secondary structure based on minimum free energy and maximum number of adjacent base pairs. This algorithm stands on a heuristic approach, which employs a dot matrix representation of all possible base pairs in RNA. Afterward, stems are extracted from the dot matrix and decreasingly sorted based on their length. Then the stems with equal length are increasingly sorted according to the free energy. Finally, the stems are orderly selected to form RNA secondary structure. The proposed algorithm is performed on some datasets containing CopA, CopT, R1inv, R2inv, Tar, Tar*, DIS, IncRNA54, and RepZ in the bacteria. Experimental results showed high accuracy of 95.71% of the proposed algorithm. This algorithm is run in lower computational time in comparison to the other similar approaches.

Keywords: Minimum free energy, Base pair, Dot matrix, Stem

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