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Updated: Feb 10, 2026

The Use of Chemostats in Microbial Systems Biology

The Use of Chemostats in Microbial Systems Biology

Published on: October 14, 2013

Modeling biological systems with uncertain kinetic data using fuzzy continuous Petri nets.

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.

BMC Systems Biology

|May 11, 2018

Summary

This study introduces fuzzy continuous Petri nets (FCPNs) to model biological systems with uncertain kinetic parameters. This approach effectively handles missing or variable data in complex biological models.

Keywords:

Fuzzy continuous Petri nets Fuzzy simulation Fuzzy uncertainties Uncertain kinetic parameters

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The Use of Chemostats in Microbial Systems Biology

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Fully Autonomous Characterization and Data Collection from Crystals of Biological Macromolecules

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Published on: March 22, 2019

Area of Science:

Systems Biology
Computational Biology
Biomathematics

Background:

Biological systems exhibit uncertainties, categorized as random and fuzzy.
Stochastic methods address random uncertainties, while fuzzy methods are needed for fuzzy uncertainties.

Purpose of the Study:

To develop a novel approach for modeling biological systems with incomplete or inaccurate kinetic parameters.
To integrate fuzzy logic with continuous Petri nets (CPNs) for enhanced modeling capabilities.

Main Methods:

Proposed a class of fuzzy continuous Petri nets (FCPNs) by combining CPNs and fuzzy logic.
Developed and implemented a simulation algorithm specifically for FCPNs.
Utilized the heat shock response system as a case study to illustrate the method's application.

Main Results:

Demonstrated the successful application of FCPNs in modeling a biological system.
The simulation algorithm for FCPNs was presented and implemented.
The heat shock response system was effectively modeled using the proposed FCPN approach.

Conclusions:

The FCPN approach provides a robust method for modeling biological systems with parameter uncertainties.
This method is applicable to systems where kinetic parameters are unavailable or fluctuate due to environmental factors.