Quantum-inspired algorithm for simulating viral response

2025/06/18 by Konina, Daria O., Korbashov, Dmitry I., Kovalchuk, Ilya V. +3
#FOS: Biological sciences #FOS: Physical sciences #Genomics (q-bio.GN) #Molecular Networks (q-bio.MN) #Quantum Physics (quant-ph)

paper · doi:10.48550/arxiv.2506.15671

Abstract

Understanding the properties of biological systems is an exciting avenue for applying advanced approaches to solving corresponding computational tasks. A specific class of problems that arises in the resolution of biological challenges is optimization. In this work, we present the results of a proof-of-concept study that applies a quantum-inspired optimization algorithm to simulate a viral response. We formulate an Ising-type model to describe the patterns of gene activity in host responses. Reducing the problem to the Ising form allows the use of available quantum and quantum-inspired optimization tools. We demonstrate the application of a quantum-inspired optimization algorithm to this problem. Our study paves the way for exploring the full potential of quantum and quantum-inspired optimization tools in biological applications.

Citations

• Coherent Ising Machines with Optical Error Correction Circuits
• Hypergraph Models of Biological Networks to Identify Genes Critical to Pathogenic Viral Response
• Lung-Derived Exosomal miR-483-3p Regulates the Innate Immune Response to Influenza Virus Infection

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