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A biological sequence comparison algorithm using quantum computers.

Büsra Kösoglu-Kind1, Robert Loredo2,3, Michele Grossi4

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This study introduces a new quantum computing method for genetic sequence analysis. It uses quantum images to precisely compare DNA sequences, offering faster and more efficient analysis than traditional methods.

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Area of Science:

  • Genomics
  • Quantum Computing
  • Bioinformatics

Background:

  • Genetic information is encoded in vast nucleotide sequences.
  • Detecting sequence differences is crucial for biology and medicine.
  • Classical computing faces challenges with large genomic datasets.

Purpose of the Study:

  • To develop a novel quantum computing approach for pairwise genetic sequence analysis.
  • To enhance the accuracy and resolution of genetic variation detection.

Main Methods:

  • Leveraging quantum computing principles inspired by visual perception and pixel representation.
  • Utilizing the Flexible Representation of Quantum Images (FRQI) framework for sequence comparison.
  • Implementing pairwise sequence analysis at the individual nucleotide or amino acid level.

Main Results:

  • Achieved fine-granularity comparisons of gene sequences.
  • Demonstrated enhanced accuracy and resolution in detecting subtle genetic variations.
  • Offered algorithmic advantages including reduced time complexity and improved space efficiency.

Conclusions:

  • The application of the FRQI algorithm to genome sequencing represents a novel approach.
  • This quantum-based method enables precise examination of genetic information at the individual letter or amino acid level.
  • The breakthrough promises to advance biological data analysis and deepen the understanding of genetic information.