DNA and Protein Sequence Alignment

Sequence alignment is a computational method used to compare two or more biological sequences (DNA, RNA, or protein) by arranging them to identify regions of similarity. For example, essential to genome analysis is mapping the billions of short nucleotides (genetic sequences/DNA reads) or amino acids (proteins) to a known reference genome. Accurate alignment is critical for next steps in the genetic analyses, such as finding evolutionary relationships, identifying genetic variants or to compare an individual's genome to a reference genome. However, it’s computationally intensive and slow on classical computers, especially with massive genomic datasets.

Quantum algorithms like Grover’s algorithm can speed up search and pattern-matching tasks by reducing the number of steps needed to find matches. The Quantum Fourier Transform (QFT) can help analyze repeating patterns in sequences more efficiently. Researchers are adapting these quantum techniques, originally developed for general data search, to genomic sequence alignment.

These quantum techniques could greatly speed up genetic analysis. This supports precision medicine, large-scale population studies, and enables the timely analysis of clinical samples. It also facilitates identifying mutations or disease markers, possibly leading to breakthroughs in personalised medicine and large-scale genomic research. This is crucial for understanding genetic diseases and drug development.