Conserved secondary structure prediction for similar highly group of related RNA sequences

Successfully predicting the conserved structure of a group of related RNAs plays an important role in identifying their functions. In this paper, we propose a new scheme to tackle this problem by using information of stem occurrence frequency. Our method was tested against ten groups of HIV-1 isolates and all ten predicted conserved secondary structures were perfectly consistent with the wild type structure. The method showed to be very efficient for similar highly RNA sequences. Besides, the time complexity of our algorithm is O(n²m²) where the group considered consists of m isolate RNA sequences and every sequence has roughly n-length nucleotide bases.