Analysis of Mycobacterium Tuberculosis, Mycobacterium Bovis, and Mycobacterium Africanum that Cause Tuberculosis Using Apriori and Decision Tree Algorithm

Abstract

About two million people die from Tuberculosis (TB) each year, and the high death rate of the disease has persisted for decades. TB infection, which is caused by bacteria that belong to genus Mycobacterium, can significantly affect normal functions of lungs and other body parts such as brain and spine. Although tuberculosis patients have been treated with medicines, it took much time to detect visible effects. To further enhance the vaccines and treatment of TB, people should conduct more comprehensive research about the TB infection. Therefore, in this research, we aim to analyze genomes of three bacteria in Mycobacterium genus: Mycobacterium tuberculosis, Mycobacterium bovis, and Mycobacterium africanum. We adopted mainly two algorithms, apriori and decision tree, in order to proceed analysis. Before we undertook an experiment, we established a hypothesis: M. tuberculosis and M. bovis would exhibit a stronger correlation because they are the most common cause of tuberculosis for a long time. By analyzing their DNA sequences and amino acid frequency, we examined relationships between those three bacteria, especially similarities and differences. Furthermore, we tried to prove the hypothesis. We expect that our research will give a chance to improve potent vaccines and medicines by adopting these relationships we found in our research.