Biomedical & Pharmacology Journal, September 2021. Vol. 14(3), p. 1567-1578 Published by Oriental Scientific Publishing Company © 2021 This is an Open Access article licensed under a Creative Commons license: Attribution 4.0 International (CC-BY). Genetic Algorithm Approach to Find the Estimated Value of HMM parametersfor NS5 Methyltransferase Protein Nidhi Katiyar 1 , Ravindra Nath 2 and Shashwat Katiyar 3 1 Dr. APJ Abdul Kalam Technical University (AKTU), Lucknow, India. 2 University Institute of Engineering, Technology, CSJM University, Kanpur,U.P., 208024, India. 3 Institute of Bioscience and Biotechnology, CSJM University, Kanpur, U.P., 208024, India. *Corresponding Author E-mail : nidhi26kanpur@gmail.com https://dx.doi.org/10.13005/bpj/2259 (Received: 07 January 2021; accepted: 03 August 2021) Dengue is the pandemic disease caused by Dengue virus (DENV), a mosquito-borne flavivirus. In recent years dengue has emerged as a foremost cause of severe illness and deaths in developing countries.About 400 million dengue infections occur worldwide each year.In general, dengue infections create only mild illness but infrequently expand into a lethal illness termed as severe dengue for which no specific treatment. The machine learning approach plays a significant role in bioinformatics and other fields of computer science.It exploitsapproaches like Hidden Markov Model (HMM), Genetic Algorithm (GA), Artificial Neural Network (ANN), and Support Vector Machine (SVM).The GA is a randomized search algorithm for solving the problem based on natural selection phenomena.Many machine learning techniques are based on HMM have been positively applied. In this work, We firstly used HMM parameters on the biological sequence,and after that, we catch the probability of the observation sequence of a mutated gene sequence. This study comparesboth methods, G.A. and HMM, to get the highest estimated value of the observation sequence. In this paper, we also discuss the applications ofGA in the bioinformatics field. In a further study, we will apply the other machine learning approaches to find the best result of protein studies. Keywords: Artificial Neural Network; Dengue; Evolutionary Algorithm; Flavivirus Genetic Algorithm; Hidden Markov model; Methyltransferase Protein; Machine Learning; Protein Data bank. Dengue virus (DV), the causative agent of dengue, resides in the family Flaviviridae and is transmitted to humans by biting Aedes aegypti mosquitoes. Four serotypes (Dengue Virus serotype 1, Dengue virus serotype 2, Dengue virus serotype 3, and Dengue virus serotype 4) are recognized (El Sahili, Lescar 2017). The range of dengue disease spans from a fu-like disease termed dengue fever to Dengue hemorrhagic fever. In chronic cases, it causes dengue shock syndrome and sometimes terminates in death. The most prevalent clinical symptoms of acute dengue disease are hemorrhagic diathesis, liver involvement, and plasma leakage. The DV genome is prepared into a single open reading frame (ORF) of single-stranded (positive -sense) RNA of 900 kDa and fanked at 5'end by type I cap and at 3'end by untranslated regions and encodes a precursor polyprotein. Post-translational modifcation of precursor protein gives rise to three structural (C, prM, and E) proteins and seven non- structural (NS1, NS2A, NS2B, NS3, NS4A, NS4B, and NS5) proteins (Anasiret al., 2020).