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Biological Sequences Comparison Based on Optical Processing

Akbari Rokn Abadi, Saeedeh | 2023

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  1. Type of Document: Ph.D. Dissertation
  2. Language: Farsi
  3. Document No: 56609 (19)
  4. University: Sharif University of Technology
  5. Department: Computer Engineering
  6. Advisor(s): Koohi, Somayyeh
  7. Abstract:
  8. Biological sequences, such as DNA, RNA, and proteins, contain vital information and activities of living organisms. Any changes or mutations in these sequences can alter the structure of proteins, which are the basis of all cell activities. This can cause disruptions in cellular functions. With advancements in cell data extraction technology, the amount of genetic data has increased, leading to a need for efficient methods to identify and study mutations. One of the primary tools for this work is biological sequence comparators. Despite the different types of sequence comparators available, there is still a need for an algorithm that is fast, accurate, scalable, and uses few resources. However, current methods face limitations, including the maximum number of sequences that can be compared, their length, speed, and accuracy. Studies show that using optical solutions could increase the speed of sequence comparison tools up to 90%, overcome memory limitations, reduce power consumption, and significantly improve output accuracy. This research aims to provide solutions for comparing biological sequences using optical technology and data processing with light. The objectives are to improve speed, accuracy, scalability, and power consumption. Several steps, from tool input to structure design, were researched to achieve these goals. Over five input image generation methods were designed to reduce pattern recognition errors and improve comparison accuracy. Additionally, three quasi-alignment, alignment, and alignment-independent comparison methods were designed that can perform all types of sequence comparison. The performance of these methods was evaluated and compared with other leading methods in the field
  9. Keywords:
  10. Optical Computing ; Biological Sequence Processing ; Alignment ; Alignment-Free Method ; Cross Correlation ; Sequence Comparison

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