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- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 55169 (19)
- University: Sharif University of Technolog
- Department: Computer Engineering
- Advisor(s): Sharifi Zarchi, Ali
- Abstract:
- Traditional techniques use invasive histology techniques to diagnose cancer. Cancer tissue is sampled directly in this method, which is very painful for the patient. In recent years, scientists have discovered that the cell world is released into the blood plasma after cell death, obtaining useful cancer information. Since methylation changes in cancer cells are very significant and the death rate of cancer cells is high, the methylation of each tissue is different from the other. Furthermore, they were diagnosing the type of cancer.On the other hand, due to the different patterns in methylated DNA with normal DNA and the use of bisulfite treatment technique to detect the degree of methylation in readings, conventional DNA leveling tools cannot align methylated DNA. If used, Common tools cause problems such as data loss. Therefore, special alignment methods must be used for this data to obtain the information of methylated doses.In the present study, we first propose a new method for aligning methylation data and comparing it with existing tools. The comparison results show the superiority of the proposed method. Then, using statistical techniques and machine learning, we implement a new way for detecting cancer and source tissue using cell-free DNA methylation data in the Python programming language
- Keywords:
- Alignment ; DNA Methylation ; Non-Invasive Measurement ; Bisulfite Treatment ; Biopsy ; Liquid Biopsy ; Cancer Diagnosis
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