Using intelligent optimization algorithms, determine the quality of the nitrogenous base substituted for the MT-ND5 gene sequence
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Keywords:
MT-ND5 gene, Ant colony optimization(ACO), Hidden Markov Model (HMM).Abstract
This paper focuses on the application of intelligent optimization techniques in genetic engineering, using the MT-ND5 gene sequence as a case study to determine the specificity of nitrogenous base substitution. We used data from the NCBI database and analyzed it using smart optimization algorithms for the mathematical model of the objective function of the type of dynamic programming that comes from the hidden Markov chain to find the chance of getting a true sequence that is highest. We compared the results with the intelligent methods, demonstrating the effectiveness of these solutions in speeding up and enhancing the accuracy of the analysis through MATLAB simulations.
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