A petri net application to model metabolic processes
Systems Analysis Modelling Simulation
Principled computational methods for the validation and discovery of genetic regulatory networks
Principled computational methods for the validation and discovery of genetic regulatory networks
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
Natural Computing: an international journal
The combinatorics of modeling and analyzing biological systems
Natural Computing: an international journal
The combinatorics of modeling and analyzing biological systems
Natural Computing: an international journal
Knowledge-Guided identification of petri net models of large biological systems
ILP'11 Proceedings of the 21st international conference on Inductive Logic Programming
On Minimality and Equivalence of Petri Nets
Fundamenta Informaticae - Concurrency, Specification and Programming
| Hi-index | 5.23 |
Models of biological systems and phenomena are of high scientific interest and practical relevance, but not always easy to obtain due to their inherent complexity. To gain the required insight, experimental data are provided and need to be interpreted in terms of models that explain the observed phenomena. In systems biology the framework of Petri nets is often used to describe models for the regulatory mechanisms of biological systems. The aim of this paper is to provide, based on results in Marwan et al. (2008) [1] and Durzinsky et al. (2008) [2], an algorithmic framework for the challenging task of generating all possible Petri nets fitting the given experimental data.