Analysis of Human Papillomavirus Using Datamining - Apriori, Decision Tree, and Support Vector Machine (SVM) and its Application Field
1 Department of Natural Science, Hankuk Academy of Foreign Studes, 50, Oedae-ro 54beon-gil, Mohyeon-myeon, Cheoin-gu, Yongin-si, Gyeonggi-do, Republic of Korea
2 Department of Computer Science and Engineering, Korea University, Seoul, Repuulic of Korea
Human Papillomavirus(HPV) has various types (compared to other viruses) and plays a key role in evoking diverse diseases, especially cervical cancer. In this study, we aim to distinguish the features of HPV of different degree of fatality by analyzing their DNA sequences. We used Decision Tree Algorithm, Apriori Algorithm, and Support Vector Machine in our experiment. By analyzing their DNA sequences, we discovered some relationships between certain types of HPV, especially on the most fatal types, 16 and 18. Moreover, we concluded that it would be possible for scientists to develop more potent HPV cures by applying these relationships and features that HPV virus exhibit.
© Owned by the authors, published by EDP Sciences, 2016
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