PUB - Publikationen an der Universität Bielefeld

Petri nets have been widely used for decades as a method to model parallel processes, particularly in the field of systems biology. Over time, the basic formalism of Petri nets has been extended with various concepts and hybrid functional Petri nets (HFPN) are suitable to represent quantitative systems as occurring in systems biology applications cases. For the temporal analysis of a model, the generation of comprehensible simulation results strictly complying with the underlying definitions of the formalism, is essential.
Another commonly used representation of biological systems are biological networks. However, they are attributed graphs without further standardization that would allow for simulation. The values of their attributes often reflect user-specific semantics. For the purpose of a meaningful simulation, universal biological networks must be transformed into a representation that allows simulation, such as Petri nets, while also considering user-specific semantics.
This thesis identifies the requirements for modeling and simulating HFPN and evaluates existing solutions accordingly. As a result, a novel open-source modeling and simulation environment VANESA 2.0, utilizing OpenModelica and PNlib, is presented. It offers reliable simulation results and incorporates a unique combination of features, with a particular emphasis on handling kinetics and their parameters, improving scalability for large-scale networks, and providing advanced visualizations of simulation results.
Moreover, this thesis addresses the challenges associated with the meaningful transformation of biological networks into Petri nets and assesses existing approaches that automate this process. In response, a customizable rule-based transformation approach, based on exact pattern matching of attributed subgraphs, is developed and presented.
To demonstrate the feasibility of the above proposed concepts, the open-source project VANESA is extended by the contributions of this thesis and is available as VANESA 2.0 at [https://github.com/cbrinkrolf/VANESA](https://github.com/cbrinkrolf/VANESA).