Petri Net Modeling in Systems Biology
Summary
Petri nets provide a formal yet visually intuitive framework for representing and analysing the structure and dynamics of biological systems. In their basic form, places denote molecular species or functional states, transitions represent biochemical reactions or events, and tokens capture the distribution of entities across the network. Extensions such as stochastic Petri nets incorporate probabilistic firing to reflect intrinsic randomness in molecular interactions, while coloured Petri nets introduce data‐rich tokens that can encode distinct molecular types or spatial coordinates. Hybrid Petri nets further blend continuous flows and discrete events to capture processes spanning multiple time scales. Together, these formalisms enable qualitative and quantitative analysis of complex phenomena such as signal transduction, gene regulation and multiscale population dynamics. Structural analysis techniques expose invariants and conserved motifs that underlie system robustness, whereas simulation and formal verification methods probe possible dynamic behaviours, including oscillations, bistability and switch‐like responses. Petri net modelling has proven instrumental in integrating heterogeneous data, guiding experimental design and supporting multilevel engineering of biomolecular networks, with applications ranging from metabolic pathway optimisation to the study of immune responses.
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Petri Net Modeling in Systems Biology publication trend
The graph below shows the total number of articles in petri net modeling in systems biology across all publications each year (not limited to Nature Index journals).
Technical terms
Petri net: A bipartite graph of places, transitions and tokens used to model concurrent systems.
Stochastic Petri net: A Petri net variant where transitions fire according to specified probability distributions.
Coloured Petri net: A high‐level Petri net that assigns data values (colours) to tokens, enabling detailed token differentiation.
Hybrid Petri net: A framework combining discrete transitions with continuous flows to represent multiscale dynamics.
References
- Protocol for biomodel engineering of unilevel to multilevel biological models using colored Petri nets. STAR Protocols (2023).
- Formal verification confirms the role of p53 protein in cell fate decision mechanism. Theory in Biosciences (2022).
- A Graphical Approach for Hybrid Simulation of 3D Diffusion Bio‐Models via Coloured Hybrid Petri Nets. Modelling and Simulation in Engineering (2020).
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