Colored Fuzzy Petri Nets for Dealing with Genetic Regulatory Networks

Fuzzy approaches play an important role in the modeling of genetic regulatory networks (GRNs) with incomplete quantitative data. However, current fuzzy approaches such as fuzzy logic and fuzzy Petri nets (FPNs) can neither clearly describe causal relationships between genes as each interaction between genes is represented by a couple of fuzzy rules, nor easily deal with large GRNs. To address these issues, this paper presents a new class of colored fuzzy Petri nets (CFPNs) by combining colored Petri nets with FPNs, which makes it possible to clearly represent interactions among genes or to construct a compact model for a large GRN requiring many fuzzy rules. We give the definition of CFPNs and a simulation approach which incorporates a reasoning algorithm, as well as a detailed procedure for modeling and analyzing GRNs with CFPNs. We illustrate our approach using a simple example comprising six genes.

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Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).