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Elsevier eBooks

Quantum algorithms for genomic analysis in systems biology

Don Roosan, Hasiba Mahshed Khan, Rubayat Islam Khan

Published Jan 1, 2026• 0 citations
Publisher
DOI
10.1016/b978-0-443-34193-9.00002-8

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This paper explores the application of quantum error correction codes (QECCs) to gene sequence analysis, addressing the limitations of traditional methods in handling high error rates and complex interactions within genomic data. We posit that gene sequences can be represented as quantum bits (qubits), and QECCs can be utilized to identify redundant information and uncover hidden patterns indicative of biological function. The core claim centers on leveraging the high error-correcting capabilities of QECCs to analyze gene sequences with significant redundancy, revealing intricate patterns and interactions previously inaccessible through conventional approaches. The proposed mechanism involves encoding gene sequences into a qubit representation and employing QECC algorithms for error detection and correction, ultimately leading to a refined understanding of genomic data. This research introduces a novel framework for gene sequence analysis, potentially accelerating discoveries in areas such as personalized medicine and evolutionary biology. The core mechanism relies on the ability of QECCs to effectively mitigate errors arising from inherent sequence variations and complex biological processes, providing a robust and potentially highly accurate method for genomic investigation. The analysis presented utilizes a simplified model for demonstration, with future work focused on adapting the techniques to larger and more complex genomic datasets.