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Quantum Modeling for Simulating Biological Stochastic Processes

Research output: Conference PapersPosterpeer-review

Abstract

Stochastic processes are fundamental in describing biological phenomena and instrumental for modeling cellular dynamics for bioengineering applications. Stochastic processes are analyzed using Monte-Carlo simulations, which are computationally intensive. We have developed a quantum representation of a biological stochastic process using P. putida NBUS12 polyhydroxylalkanoate (PHA) biosynthesis as a case study, and established a framework towards utilizing the power of quantum computing to simulate biological phenomena.
Original languageEnglish
Publication statusPresented - 2024
EventQuantum Computing and Artificial Intelligence Applications Workshop - Copenhagen, Denmark
Duration: 6 May 20248 May 2024

Conference

ConferenceQuantum Computing and Artificial Intelligence Applications Workshop
PlaceDenmark
CityCopenhagen
Period6/05/248/05/24

Funding

This work is supported by a General Research Fund funded by Research Grants Council, Hong Kong (GRF/RGC 17208121) and a University Grants Committee Research Matching Grant Scheme (UGC-RMGS), Hong Kong.

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