A DNA sequence alignment algorithm using quality information and a fuzzy inference method

DNA sequence alignment algorithms in computational molecular biology have been improved by diverse methods. In this paper, we propose a DNA sequence alignment that uses quality information and a fuzzy inference method developed based on characteristics of DNA fragments and a fuzzy logic system in order to improve conventional DNA sequence alignment methods that uses DNA sequence quality information. In conventional algorithms, DNA sequence alignment scores are calculated by the global sequence alignment algorithm proposed by Needleman-Wunsch, which is established by using quality information of each DNA fragment. However, there may be errors in the process of calculating DNA sequence alignment scores when the quality of DNA fragment tips is low, because only overall DNA sequence quality information are used. In our proposed method, an exact DNA sequence alignment can be achieved in spite of low quality of DNA fragment tips by improvement of conventional algorithms using quality information. Mapping score parameters used to calculate DNA sequence alignment scores are dynamically adjusted by the fuzzy logic system utilizing lengths of DNA fragments and frequencies of low quality DNA bases in the fragments. From the experiments by applying real genome data of National Center for Biotechnology Information, we could see that the proposed method is more efficient than conventional algorithms.