Comparative Literature Survey on Quantum Computing Approaches for Genome Assembly and Sequence Analysis
Abstract
The explosive growth of genomic information calls for computational methods to handle complex sequence analysis
and genome assembly assays. Based on the principles of superposition and entanglement, quantum computing represents an
another way of computation to achieve potentially faster and more efficient operations than classical systems. This article offers
a comparative overview of 4 major studies dedicated to the use of QC in genomics, spanning theoretical algorithmical
conceptualization, systematic literature mapping, analyses on practical challenges in QC-aided genomics and hybrid Q-C
designs. The review indicates that there is potential for significant speed-up based on theoretical formulation, while current
applications are limited by hardware resource constraint, data-loading latency and scalability. Hybrid models, in particular those
that hybridize quantum annealing with classical optimization, seem to offer the most practicable route to near-term genomic
computing. The analysis also shines a light on the increasingly pivotal positions that quantum-inspired approaches and hybrid
orchestration systems are playing as crucial stepping stones towards full-quantum advantage. The results suggest that quantum
computing is in its infancy as far as genomic analysis is concerned but the potential seems to be promising for future
bioinformatics research and applications. Such opportunities are only accessible with further advancements in quantum
hardware, data encoding and…
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