Author
Abstract
The convergence of DNA sequencing and digital hardware technologies represents a transformative frontier in genomics research, accelerating capabilities while reducing costs and increasing accessibility. Next-Generation Sequencing (NGS) technologies have dramatically increased genetic data volume, creating computational challenges that traditional systems struggle to address efficiently. Specialized hardware accelerators, including Graphics Processing Units (GPU) and Field-Programmable Gate Arrays (FPGA), provide customizable acceleration for genomic algorithms with superior energy efficiency. Custom silicon solutions like Application-Specific Integrated Circuits (ASICs) and System-on-Chip (SoC) designs minimize data transfer bottlenecks and enable point-of-care genetic analysis. Additionally, Neural Processing Units (NPUs) embedded in sequencing systems enable real-time pattern recognition while reducing false positives, and machine-learning hardware accelerators improve base-calling accuracy through adaptive error correction. These technological advances have significant impacts on healthcare through personalized medicine advancements, enabling routine whole-genome analysis in clinical settings with faster turnaround times, while research capabilities benefit from dramatically improved processing capabilities that make previously impractical analyses feasible.
Suggested Citation
Sruthi Somarouthu, 2025.
"DNA Sequencing and Digital Hardware: Pushing the Boundaries of Genomics,"
Journal of Computer Science and Technology Studies, Al-Kindi Center for Research and Development, vol. 7(5), pages 35-42, May.
Handle:
RePEc:alk:jcsts0:v:7:y:2025:i:5:id:9759
DOI: 10.32996/jcsts.2025.7.5.5
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