Composition Colored Petri Nets for the Refinement of Reaction-based Models



: Diana-Elena Gratie, Cristian Gratie

Publisher: ELSEVIER SCIENCE BV

: 2016

: Electronic Notes in Theoretical Computer Science

: ELECTRONIC NOTES IN THEORETICAL COMPUTER SCIENCE

: ELECTRON NOTES THEOR

: 326

: 51

: 72

: 22

: 1571-0661

DOI: https://doi.org/10.1016/j.entcs.2016.09.018


Model refinement is an important step in the model building process. For reaction-based models, data refinement consists in replacing one species with several of its variants in the refined model. We discuss in this paper the implementation of data refinement with Petri nets such that the size of the model (in terms of number of places and transitions) does not increase. We capture the compositional structure of species by introducing a new class of Petri nets, composition Petri nets (ComP-nets), and their colored counterpart, colored composition Petri nets (ComCP-nets). Given a reaction-based model with known compositional structure, represented as a ComP-net, we propose an algorithm for building a ComCP-net which implements the data refinement of the model and has the same network structure as the initial ComP-net.



Last updated on 2024-26-11 at 10:49