Various algorithms have been developed to find an optimal alignment between the biological sequences DNA and RNA. Some of them use the traditional dynamic programming algorithms that produce highly accurate and optimal alignments at the cost of high computational complexity. To lower the computational cost of aligning the sequences, few algorithms have exploited the mathematical transform principles like the Fourier transform on the sequences encoded into numerical values.; This research evaluates the utility of exploiting wavelet transform principles on the encoded sequences, for finding an optimal alignment between them. The technique follows the dynamic programming algorithm on a restricted area unfolded by the correlation graph of the transformed sequences. Furthermore, the experimental studies show the trade-off accuracy versus computational speedup.
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