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DNA Classification Using Optical Processing based on Alignment-free Methods

Kalhor, Reza | 2021

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 53702 (19)
  4. University: Sharif University of Technology
  5. Department: Computer Engineering
  6. Advisor(s): Koohi, Somayyeh
  7. Abstract:
  8. In this research, an optical processing method for DNA classification is presented in order to overcome the problems in the previous methods. With improving in the operational capacity of the sequencing process, which has increased the number of genomes, comparing sequences with a complete database of genomes is a serious challenge to computational methods. Most current classification programs suffer from either slow classification speeds, large memory requirements, or both. To achieve high speed and accuracy at the same time, we suggest using optical processing methods. The performance of electronic processing-based computing, especially in the case of large data processing, is usually limited by the high power consumption and low sequential processing speed. In the proposed method, a method based on alignment-free methods works in such a way that first we break each sequence in the data-set into small blocks, then each block is encoded into an image. In the following, using an optical structure and an optimal method to minimize the time of placement of images in the proposed optical structure, the two sequences are compared. The method is that the optical processing of a pair of possible blocks compares two sequences. Finally, the output image of the optical processing is used to obtain the distance between the two sequences after applying a threshold value to image's pixels. Using the values of the distance between pairs of sequences in the data-set, a classification is provided for it. Among the existing methods for classification, methods such as vector based and ClustalW have provided good values in terms of time and accuracy. The proposed method offers much less execution time compared to the vector-based method and the ClustalW method. While it has provided good accuracy for classification and in some cases even the accuracy of the proposed method is higher than other methods, these results show the excellent performance of the proposed method
  9. Keywords:
  10. Bioinformatics ; Optical Computing ; DNA Sequencing ; Genome Comparison ; Metagenomics ; Alignment-Free Method ; DNA Classification

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