Intuitive Modeling of Dynamic Systems with Petri Nets and Fuzzy Logic

Current approaches in modeling dynamic biological systems often lack comprehensibility, especially for users without mathematical background. We propose a new approach to overcome such limitations by combining the graphical representation provided by the use of Petri nets with the modeling of dynamics by powerful yet intuitive fuzzy logic based systems. The mathematical functions and formulations typically used to describe or quantify dynamic changes of systems are replaced by if-then rules, which are both easy to read and formulate. Precise values of kinetic constants or concentrations are substituted by more natural fuzzy representations of entities. We will show that our new approach allows a semi-quantitative modeling of biological systems like signal transduction pathways or metabolic processes while not being limited to those cases.