A Pattern Detection Technique of L-MYC for Lungs Cancer Oncogene in Bioinformatics Big Data

Lung cancer; also known as lung carcinoma, is one of the fatal diseases in the field of medical science. It is occurred due to unrestrained enlargement of the cells in the tissues of the lungs. This growth is expended outside the lungs due to the process of metastasis. There are different causes of lung cancer like tobacco smoking, Radon gas, Air pollution, Asbestos, and Genetics, etc. In this paper; the L-MYC genetics is under consideration that works as a Transcription Factor (TF) in the human body and controls the appearance of the multiple genes. Rearrangement or amplification in the L-MYC gene causes B-CELL leukemia and lung cancer. This paper deals with pattern detection of L-MYC oncogene by using Big data analytics techniques and to explore those motifs that are the major causes of lung cancer. Firstly, the verification and validation of the pattern detection technique is performed by the VDM-SL. After applying the formal methods; the corresponding implementation is done in the MEME suite and Motif Finder tool that is used in order to detect the oncogene motifs in bioinformatics.