This work presents a platform for the modelling, simulation and automatic parametrization of semi-quantitative metabolic networks. Starting from a network modelled through Petri Nets (PN) and represented in SBML, the platform converts the model into an internal representation implemented through an Electronic Design Automation (EDA) description language. It applies techniques and tools well established in the EDA field to simulate the model and to automate the network parametrization. We present the validation of the model simulation and of the parameters automatically extrapolated by the platform with the state of art modelling and simulation tools for PNs. The validation uses a real metabolic network and shows the platform opportunities and limitations in reproducing the experimental results, simulating the models in different conditions, and facilitating the analysis of the dynamics that regulate the network. © Springer Nature Switzerland AG 2020.

On the Simulation and Automatic Parametrization of Metabolic Networks Through Electronic Design Automation

Bombieri, Nicola;Mastrandrea, Antonio;Scaffeo, Silvia;Caligola, Simone;Fummi, Franco;Laudanna, Carlo;Constantin, Gabriela;Giugno, Rosalba
2020

Abstract

This work presents a platform for the modelling, simulation and automatic parametrization of semi-quantitative metabolic networks. Starting from a network modelled through Petri Nets (PN) and represented in SBML, the platform converts the model into an internal representation implemented through an Electronic Design Automation (EDA) description language. It applies techniques and tools well established in the EDA field to simulate the model and to automate the network parametrization. We present the validation of the model simulation and of the parameters automatically extrapolated by the platform with the state of art modelling and simulation tools for PNs. The validation uses a real metabolic network and shows the platform opportunities and limitations in reproducing the experimental results, simulating the models in different conditions, and facilitating the analysis of the dynamics that regulate the network. © Springer Nature Switzerland AG 2020.
978-3-030-63060-7
EDA; Metabolic network; Modelling; Parametrization; Simulation
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/1056295
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