Pairwise local alignment using wavelet transform

The first fact of sequence analysis is sequence alignment, which is in turn pave the way for structural and functional analysis of the molecular sequence. Owing to the increase in biological data, the alignment approaches take more time for computation. Focusing this issue, in this work the local alignment is made for pairwise molecular sequences by applying a wavelet transform based approach (WMSA) to solve the alignment problem. Like global alignment, local alignment also gives more peculiar information of molecular sequences. Here, the sequence is converted into numerical values using the electron-ion interaction potential model. This in turn decomposed using one of the wavelet transform types and the similarity between the sequences is found using the cross-correlation measure. The significance of the similarity is evaluated using two scoring function namely Position Weight Matrix (PSM) and a new function called Count Score. The work is compared with the standard Smith-Waterman algorithm. The result shows that the proposed approach improves the speed without sacrificing the accuracy.