Hidden Markov Modelling for Biological Sequence

With 9.6 million deaths worldwide in 2018, Cancer was the second leading cause of mortality. Cancer incidence rates for about one out of every six global deaths. Consequently, progressive activities to prevent the malignancy of cells are gradually increasing. Using several stochastic models, researchers recently attempted to anticipate cancer. Those efforts relied on records containing patient malady to predict cancer earlier. This work will provide a new detain to identify malignant diseases earlier by analysing the gene sequences. The HMM is built and trained to predict the future. Machine learning algorithms have also been proposed and claimed to be able to identify disease; generalized gene sequence of the affected gene(s) is also provided. If the gene mutation has been discovered early enough, it can be used as a low-cost primary cancer treatment resistance preventive approach.