A petri net application to model metabolic processes
Systems Analysis Modelling Simulation
Concurrency and Automata on Infinite Sequences
Proceedings of the 5th GI-Conference on Theoretical Computer Science
A Partial Granger Causality Approach to Explore Causal Networks Derived From Multi-parameter Data
CMSB '08 Proceedings of the 6th International Conference on Computational Methods in Systems Biology
A Combinatorial Approach to Reconstruct Petri Nets from Experimental Data
CMSB '08 Proceedings of the 6th International Conference on Computational Methods in Systems Biology
Bisimulation equivalence of a BPP and a finite-state system can be decided in polynomial time
Electronic Notes in Theoretical Computer Science (ENTCS)
An algorithmic framework for network reconstruction
Theoretical Computer Science
Natural Computing: an international journal
The combinatorics of modeling and analyzing biological systems
Natural Computing: an international journal
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The context of this work is the reconstruction of Petri net models for biological systems from experimental data. Such methods aim at generating all network alternatives fitting the given data. To keep the solution set small while guaranteeing its completeness, the idea is to generate only Petri nets being “minimal” in the sense that all other networks fitting the data contain the reconstructed ones. In this paper, we consider Petri nets with extensions in two directions: priority relations among the transitions of a network in order to allow modeling deterministic systems, and control-arcs in order to represent catalytic or inhibitory dependencies. We define a containment relation for Petri nets taking both concepts, priority relations and control-arcs, into account. We discuss the consequences for this kind of Petri nets differing in their sets of control-arcs and priority relations, and the impact of our results towards the reconstruction of such Petri nets.