A Comparative Analysis of the Evolution of DNA Sequencing Techniques along with the Accuracy Prediction of a Sample DNA Sequence Dataset using Machine Learning

DNA is widely considered the blueprint of life. The instructions required for all life forms, to evolve, breed, and thrive are found in DNA. Deoxyribonucleic acid, more commonly known as DNA, is among the most essential chemicals in living cells. A biological macro-molecule is DNA, also known as deoxyri-bonucleic acid. Life’s blueprint is encoded by it. Sequencing of DNA has exponentially progressed due to the immense increase in data production in today’s world. By means of this paper, we intend to evaluate the evolution of DNA Sequencing methods and perform a comparative analysis of modern-day DNA sequencing techniques to the ones of the past. We also illuminate the potential of machine learning in this domain by taking an exploratory and predicting the DNA Sequence using a Multinomial Naive Bayes classifier.