Fuzzy Petri nets for modelling of uncertain biological systems. (27th December 2018)

• Record Type: Journal Article
• Authors: Liu, Fei; Heiner, Monika; Gilbert, David
• Is Part Of: Briefings in bioinformatics. Volume 21:Number 1(2020)
• Page Start: 198
• Page End: 210
• Publication Date: 2018-12-27
• Subjects: fuzzy Petri nets -- structural uncertainty -- parametric uncertainty -- uncertain biological systems; Genetics -- Data processing -- Periodicals; Molecular biology -- Data processing -- Periodicals; Genomes -- Data processing -- Periodicals; 572.80285
• DOI: 10.1093/bib/bby118
• Languages: English
• ISSNs: 1467-5463

Abstract

Abstract: The modelling of biological systems is accompanied with epistemic uncertainties that range from structural uncertainty to parametric uncertainty due to such limitations as insufficient understanding of the underlying mechanism and incomplete measurement data of a system. Fuzzy logic approaches such as fuzzy Petri nets (FPNs) are effective in addressing these issues. In this paper, we review FPNs that have been used for modelling uncertain biological systems, which we classify in three categories: basic fuzzy Petri nets, fuzzy quantitative Petri nets and Petri nets with fuzzy kinetic parameters. For each category of these FPNs, we summarize its modelling capabilities and current applications, discuss its merits and drawbacks and give suggestions for further research. This understanding on how to use FPNs for modelling uncertain biological systems will assist readers in selecting appropriate FPN classes for specific modelling circumstances. This review may also promote the extensive research and application of FPNs in the systems biology area.