Photonic Quantum Computing for RNA Structure and Gene Regulation

Ribonucleic acids (RNA) play a crucial role in the post-transcriptional regulation of gene expression in cellular metabolic processes. However, analysing their structures and interactions, which are often represented as graph-based problems, poses complex, computationally intensive challenges. Gaussian Boson Sampling (GBS), a photonic quantum computational technique, offers a promising solution beyond the capabilities of classical algorithms. This work investigates the applications of GBS in RNA folding prediction and multi-omics analysis, specifically across transcriptomic and proteomic levels, to address structural and functional relationships in gene regulation. Additionally, we discuss current hardware limitations and future directions for advancing the technology. By bridging quantum computing and molecular biology, this interdisciplinary approach provides transformative opportunities for both fields.