DNA Sequence Alignment Algorithm Based on k-tuple Statistics

Abstract

DNA Sequence Alignment is one of the most basic and most important operations in bioinformatics. In this paper, we put forward to SDkS algorithm based on k-tuple statistic, which is a kind of probability method. The positive transition probability matrix, the negative transition probability matrix, and the logarithmic ration are computed based on Markov model. After obtaining converting sequence, we get the results of k-tuple statistic. Subsequently, the similarity measurement can be gained according to above parameters. When the minimum support is given, we can identify two DNA sequences is similarity or not. The experimental results show that SDkS algorithm has better effective performance in saving computing time.