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In this manual we discuss the use of Snoopy’s computational steering framework to simulate and interactively steer (stochastic, continuous, hybrid) Petri nets, e.g., biochemical network models. In a typical application scenario, a user constructs a model using a Petri net editing tool (e.g., Snoopy). Afterwards, the Petri net model is submitted to one of the running servers to quantitatively simulate it. Later, other users can adapt their steering GUIs to connect to this model. One of the connected users initialises the simulation while others could stop, pause, or restart it. When the simulator initially starts, it uses the current model settings to run the simulation. Later, other users can remotely join the running simulation and change on the fly parameters and the current marking.
Modeling plays a crucial role in Systems Biology in order to provide a system-level understanding of biological systems. With the rapid development of systems biology, modeling of biological systems has shifted from single scales to multiple scales. This introduces a series of challenges that should be addressed, e.g. repetition of components such as genes and cells, variation of components, or hierarchical organization of components. Traditional modeling approaches, e.g. Petri nets, cannot afford to cope with these challenges, which, however, can be tackled using colored Petri nets. This thesis aims to present a technology based on colored Petri nets and associated techniques to address challenges introduced by multiscale modeling in systems biology and to implement them in our modeling tool, Snoopy. To this aim, we present a colored Petri net framework for systems biology, which relates three modeling paradigms: colored qualitative Petri net (QPNC), colored stochastic Petri net (SPNC) and colored continuous Petri net (CPNC). Using this framework, we can model and analyze a biological system from three different perspectives: qualitative, stochastic and continuous by converting them into each other. We implement this framework in our modeling tool, Snoopy, and therefore in this thesis we explore three key problems concerning the implementation of colored Petri nets. For animating/simulating colored Petri nets, we present an efficient algorithm for the computation of enabled transition instances. In order to utilize the analysis techniques of Petri nets we present an efficient unfolding algorithm for large-scale colored Petri nets. In addition, we discuss three special cases for automatic folding (colorizing): colorizing T-invariants, master nets and twin nets in order to reduce the amount of work for folding Petri nets. Petri nets offer a large variety of analysis techniques ranging from informal techniques, e.g. animation/simulation to formal techniques, e.g. model checking. We summarize those analysis techniques that can be used for colored Petri nets, e.g. structural analysis, numerical and simulative model checking from the application point of view. We discuss some scenarios to illustrate the potential capability of colored Petri nets to cope with challenges in systems biology. Moreover, we apply our colored Petri net technology and techniques to three case studies, C. elegans vulval development, coupled Ca2+ channels and membrane systems. These case studies not only demonstrate how to use the colored Petri net framework and related analysis techniques for modeling and analyzing biological systems, but also show how to address the challenges of systems biology.