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

Saeedeh Akbari Rokn Abadi, Negin Hashemi Dijujin and Somayyeh Koohi

PLOS ONE, 2021, vol. 16, issue 1, 1-27

Abstract: 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.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0245095

DOI: 10.1371/journal.pone.0245095

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