A Novel Statistical Cut-Strategy for DP-based Multiple Biosequence Alignment

Abstract

In this paper, a novel cut-strategy is presented for solving the problems of multiple biosequence alignment. Sequence comparison is the most important primitive operation for analyzing of the bioinformatics data. The most fundamental method for alignment of several biosequences is the dynamic programming (DP) technique. The DP method is capable of finding optimal alignments for a set of sequences. However, when the length of the sequences increased, the DP method is impracticable due to the computational complexity is extremely high. Therefore, a new method is proposed in this paper for reducing the computational cost of the DP technique. By recursively finding the structural features of the biosequences, the proposed method can divide the biosequences into very small alignment problem, which can be directly solved by DP, or other applicable methods that can produce the results of alignment faster. By utilizing the object-oriented programming technique, the proposed method also provides low memory space consumption during execution. Moreover, the proposed algorithm has been implemented in an x86 demonstration program, and compares the effective and efficient performance with other known method.