A biological sequence comparison algorithm using quantum computers

Fuente: arXiv
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Autori principali: Kösoglu-Kind, Büsra, Loredo, Robert, Grossi, Michele, Bernecker, Christian, Burks, Jody M, Buchkremer, Rudiger
Natura: Preprint
Pubblicazione: 2023
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author Kösoglu-Kind, Büsra
Loredo, Robert
Grossi, Michele
Bernecker, Christian
Burks, Jody M
Buchkremer, Rudiger
author_facet Kösoglu-Kind, Büsra
Loredo, Robert
Grossi, Michele
Bernecker, Christian
Burks, Jody M
Buchkremer, Rudiger
contents Genetic information is encoded in a linear sequence of nucleotides, represented by letters ranging from thousands to billions. Mutations refer to changes in the DNA or RNA nucleotide sequence. Thus, mutation detection is vital in all areas of biology and medicine. Careful monitoring of virulence-enhancing mutations is essential. However, an enormous amount of classical computing power is required to analyze genetic sequences of this size. Inspired by human perception of vision and pixel representation of images on quantum computers, we leverage these techniques to implement a pairwise sequence analysis. The methodology has a potential advantage over classical approaches and can be further applied to identify mutations and other modifications in genetic sequences. We present a method to display and analyze the similarity between two genome sequences on a quantum computer where a similarity score is calculated to determine the similarity between nucleotides.
format Preprint
id arxiv_https___arxiv_org_abs_2303_13608
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle A biological sequence comparison algorithm using quantum computers
Kösoglu-Kind, Büsra
Loredo, Robert
Grossi, Michele
Bernecker, Christian
Burks, Jody M
Buchkremer, Rudiger
Quantum Physics
Genomics
Genetic information is encoded in a linear sequence of nucleotides, represented by letters ranging from thousands to billions. Mutations refer to changes in the DNA or RNA nucleotide sequence. Thus, mutation detection is vital in all areas of biology and medicine. Careful monitoring of virulence-enhancing mutations is essential. However, an enormous amount of classical computing power is required to analyze genetic sequences of this size. Inspired by human perception of vision and pixel representation of images on quantum computers, we leverage these techniques to implement a pairwise sequence analysis. The methodology has a potential advantage over classical approaches and can be further applied to identify mutations and other modifications in genetic sequences. We present a method to display and analyze the similarity between two genome sequences on a quantum computer where a similarity score is calculated to determine the similarity between nucleotides.
title A biological sequence comparison algorithm using quantum computers
topic Quantum Physics
Genomics
url https://arxiv.org/abs/2303.13608