Quantum-inspired algorithm for simulating viral response

TL;DR

This paper presents a proof-of-concept study applying a quantum-inspired optimization algorithm to simulate viral response by modeling gene activity patterns with an Ising-type model, demonstrating potential for biological applications.

Contribution

It introduces a novel application of quantum-inspired optimization to biological systems, specifically modeling viral response through an Ising-type framework.

Findings

Successful formulation of gene activity patterns as an Ising model

Application of quantum-inspired algorithms to biological simulation

Paves the way for future quantum-based biological research

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.