Modeling biological systems with uncertain kinetic data using fuzzy continuous Petri nets
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Updated: Feb 10, 2026

The Use of Chemostats in Microbial Systems Biology
Published on: October 14, 2013
Fei Liu1, Siyuan Chen2, Monika Heiner3
1School of Software Engineering, South China University of Technology, Guangzhou, 510006, People's Republic of China. feiliu@scut.edu.cn.
Background:
Uncertainties exist in many biological systems, which can be classified as random uncertainties and fuzzy uncertainties. The former can usually be dealt with using stochastic methods, while the latter have to be handled with such approaches as fuzzy methods.
Results:
In this paper, we focus on a special type of biological systems that can be described using ordinary differential equations or continuous Petri nets (CPNs), but some kinetic parameters are missing or inaccurate. For this, we propose a class of fuzzy continuous Petri nets (FCPNs) by combining CPNs and fuzzy logics. We also present and implement a simulation algorithm for FCPNs, and illustrate our method with the heat shock response system.
Conclusions:
This approach can be used to model biological systems where some kinetic parameters are not available or their values vary due to some environmental factors.
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