Speaker
Description
An essential step of any modelling effort is to decide which parts of a system should be represented. This decision is implicitly influenced by the experimental questions we ask and hypotheses we make, which in turn determine which aspects of a system are relevant to include in a model. Less explored however is how the choice of modelling formalism itself influences what gets to be represented. Here I focus on reaction networks and Petri nets as two modelling formalisms commonly used across systems biology. Both are based on the framework of graphs and are used to model ecological and biochemical systems, sometimes interchangeably. While they are both able to represent the same processes, they do so differently. A precise comparison of how each formalism is defined at the mathematical level further reveals that reaction networks are in fact a class of the more general Petri nets, contrary to their usually claimed equivalence. Concretely, these differences illustrate different strategies in how to represent system properties, which are built into the formalism definition. The higher generality of Petri nets therefore provides a practical case of how formalisms can limit how accurately a system can be represented. Overall this work suggests ways to define more precise and general formalisms, which I will demonstrate using the abstraction of hypergraphs.
