QUICK-DNA
Full Title
QUantum Innovation for Computational Knowledge in DNADescription
The project explores how quantum computing can improve the efficiency of genome sequence alignment, one of the most computationally demanding tasks in modern bioinformatics. Next Generation Sequencing (NGS) technologies generate massive volumes of DNA data whose growth is outpacing the evolution of classical computing hardware, creating an urgent need for faster and more scalable alignment methods.
The project investigates hybrid quantum–classical approaches based on Grover’s algorithm and QAOA to accelerate DNA alignment while addressing one of the main limitations of current quantum approaches: the handling of gaps and out-of-phase regions between sequences. QUICK-DNA proposes recursive partitioning and local alignment strategies that combine quantum search with established classical bioinformatics techniques, aiming to improve both efficiency and alignment quality.
By benchmarking accuracy, scalability, runtime, and computational resource usage against state-of-the-art classical methods, the project seeks to advance the application of quantum computing in genomics and contribute to the development of more sustainable and efficient computational methods for biomedical research.