M.Sc. Tezi Görüntüleme

      Bioinformatics studies have focused on genetic disease research, disease detection and DNA sequencing methods in order to find solutions to detected diseases. The main problems in the analysis of genetic data arise from the complexity of these data sequences due to their size. This complexity is due to the data reading error made by Next Generation Sequencing ,YND, devices. Since large data arrays cannot be read at once, data can be sequenced in chunks. With the help of YND devices, it has been made possible to read large genetic data. In addition, YND devices perform erroneous reading between 1% and 3% during the reading of genetic data sequences. In this study, a method for the detection of Braf Murin Sarcoma Viral Oncogene Homologous B1 gene mutation, which is one of the most common cancer diseases today, has been proposed. In this method, the healthy BRAF gene shared through the National Biotechnology Information Center was used. Synthetic data were produced proportional to the error rates by simulating YND readings. The faulty gene was read at the specified depth size and recorded in fasta format. The sequences were compared with the reference sequence, errors were detected and corrections were applied.