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Optical pattern generator for efficient bio-data encoding in a photonic sequence comparison architecture

Akbari Rokn Abadi, S ; Sharif University of Technology | 2021

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  1. Type of Document: Article
  2. DOI: 10.1371/journal.pone.0245095
  3. Publisher: Public Library of Science , 2021
  4. Abstract:
  5. In this study, optical technology is considered as SA issues’ solution with the potential ability to increase the speed, overcome memory-limitation, reduce power consumption, and increase output accuracy. So we examine the effect of bio-data encoding and the creation of input images on the pattern-recognition error-rate at the output of optical Vander-lugt correlator. Moreover, we present a genetic algorithm-based coding approach, named as GAC, to minimize output noises of cross-correlating data. As a case study, we adopt the proposed coding approach within a correlation-based optical architecture for counting k-mers in a DNA string. As verified by the simulations on Salmonella whole-genome, we can improve sensitivity and speed more than 86% and 81%, respectively, compared to BLAST by using coding set generated by GAC method fed to the proposed optical correlator system. Moreover, we present a comprehensive report on the impact of 1D and 2D cross-correlation approaches, as-well-as various coding parameters on the output noise, which motivate the system designers to customize the coding sets within the optical setup. © 2021 Akbari Rokn Abadi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
  6. Keywords:
  7. Adenine ; Bacterial DNA ; Cytosine ; Guanine ; Case study ; Cross correlation ; Data accuracy ; Genetic algorithm ; Image processing ; Information processing ; Nonhuman ; Pattern recognition ; Photonics ; Salmonella ; Sensitivity analysis ; Velocity ; Whole genome sequencing
  8. Source: PLoS ONE ; Volume 16, Issue 1 , 2021 ; 19326203 (ISSN)
  9. URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0245095