Analysis of anti-cancer cytokines by Apriori algorithm, decision tree, and SVM

Cancer is currently a major cause of death, which resulted in great interest in the mechanisms of this disease, and how to prevent or cure it. Certain cytokines are spotlighted to be a key to solving this problem, since they play a role in the immune system against cancer. Thus, our goal is to analyze various cytokines and to mine their rules. In this study, we aimed to mine a common rule between anti-cancer cytokines: Interferon-gamma (INF-gamma), Tumor Necrosis Factor (TNF), Transforming Growth Factor beta (TNF-beta), Interleukin-2 (IL-2) and Interleukin-10 (IL-10). We analyzed their mRNA sequences using three kinds of algorithms: Apriori, Decision tree, and Support Vector Machine (SVM). We hope to contribute to finding new rules or hints to determine whether a certain cytokine may have anti-cancer properties, and thus help further studies concerning this subject.