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Analysis in Antitumor Mechanism with mTORusing Apriori Algorithm

Hyun Kwon, Yerin Oh, and Taeseon Yoon
Hankuk Academy of Foreign Studies/Natural Science, Yong-in, Republic of KOREA
Abstract―Nowadays, mTOR is expected to be an evidence to find out the origin of cancer and is being considered as a method of new medical technology. As mTOR has many roles, we speculated this is because of its components. Thus, we concatenated computer algorithm to discover mTOR. We used Apriori Algorithm which is an algorithm for frequent item set mining and association rule learning over transactional databases. For this, we divided sections into four, especially 7, 9, 13, 17 windows. According to the windows, we could analyze that leucine was the most dominant component and alanine and glutamic acid comes after with a low percentage. Leucine revitalizes mTOR much more actively, and that is the reason why leucine has the highest ratio of it. Additionally, glutamic acid and alanine interacts with each other to activate metabolism for making a cycle.
Index Terms―Apriori, mTOR, Antitumor Mechanism, leucine, Glutamic acid, Alanine

Cite: Hyun Kwon, Yerin Oh, and Taeseon Yoon, "Analysis in Antitumor Mechanism with mTORusing Apriori Algorithm," Journal of Medical and Bioengineering, Vol. 5, No. 1, pp. 72-75, February 2016. Doi: 10.12720/jomb.5.1.72-75
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