FURI | Fall 2025

Developing an Efficient Bioinformatics Tool for Sequence Alignment

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Massive genomic datasets require efficient sequence alignment to identify genetic variations and disease markers. Current tools face scalability and performance limitations when processing large biological data. The research focuses on developing an optimized sequence alignment tool that integrates algorithmic enhancements and parallel computing to improve processing speed without reducing accuracy. A prototype implemented using Biopython demonstrates the feasibility of the approach and guides further optimization. The outcome aims to accelerate genomic analysis, enabling advancements in personalized medicine, evolutionary biology, and computational health.