DNA sequence recognition based on the Markov model

DNA sequences recognition is a key problem in bioinformatics and biomedical informatics. In this paper, we solve this problem by use of the probability method and metric instead of traditional frequency metric because the characters in DNA alphabet set meet the Markov properties. For this purpose, transition probabilities, transition matrixes, and log odds ratios are defined. And then, we put forward our sequence recognition algorithm based on the Markov model (SRM), which has better performance on time complexity than some sequence alignment algorithms in the same field. The results of the contrast experiments show that our SRM algorithm can recognize DNA sequences correctly and effectively without any ambiguities.