"QuantumAligner_Datasets_Pfizer"

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Authors: Konstantinos Georgiou, Andreas Kalogeropoulos, Konstantinos P. Prousalis
Cited by: 0

Abstract

"A novel quantum algorithm for use in Biological Sequence Alignment is presented and analyzed. The large amounts of data extracted from genome sequencing, de novo assembly sequencing, resequencing, and transcriptome sequencing at the DNA or RNA level, foreshadow the need for higher computing power as well as more sophisticated alignment methods. Modern and faster sequencing techniques in genomics have led to the reconsideration of current methods of designing or implementing alignment protocols. Novel quantum computing accelerators may provide drastic solutions in this field reaching the desired levels of gate operation maturity. This paper proposes a computer vision-based approach, using the unprecedented power of entanglement in a dot-matrix, to address the high demand for fast harnessing of biological data. A quantum accelerated protocol is demonstrated and tested using the Qiskit software framework of IBM. Runtime tests verify the expectations to obtain a potentially advantageous sequence alignment algorithmic process in terms of accuracy, completeness and computing complexity. The performance has been tested under various conditions and promises a clear and viable advantage."

Fields of Study & Subjects

Quantum Computing Algorithms and Architecture Genomics and Phylogenetic Studies Fractal and DNA sequence analysis

Publication details

Journal / source
IEEE DataPort
Publication date
1 March 2026
Language
EN
Document type
Dataset