Employment of Hidden Markov Model in Determining the Quality of Nitrogenous Base Substituted of MT-ND5 gene Sequence in Humans and Mice
Abstract
Hidden Markov models were developed to analyze bioinformatics data that have attracted the attention of researchers because of their critical importance in the life of living organisms. The aim of this paper was to determine the quality of the nitrogenous base substituted for the MT-ND5 gene chain of humans and mice. The proposed algorithm using the Viterbi algorithm in the Hidden Markov model proved to be good in determining the quality of the nitrogenous base substituted for the MT-ND5 gene chain of humans and mice, depending on the high match ratios obtained and the low sum of squared errors. A computer program was designed for this purpose and the algorithm was programmed in MATLAB R2017b language, and from the practical application of the algorithm it is seen that the Hidden Markov model is a particularly powerful approach to determine the match ratio up to a high classification accuracy.
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