On the Use of Stochastic Petri Nets in the Analysis of Signal Transduction Pathways for Angiogenesis Process

In this paper we consider the modeling of a selected portion of signal transduction events involved in the angiogenesis process. The detailed model of this process contains a large number of parameters and the data available from wet-lab experiments are not sufficient to obtain reliable estimates for all of them. To overcome this problem, we suggest ways to simplify the detailed representation that result in models with a smaller number of parameters still capturing the overall behaviour of the detailed one. Starting from a detailed stochastic Petri net (SPN) model that accounts for all the reactions of the signal transduction cascade, using structural properties combined with the knowledge of the biological phenomena, we propose a set of model reductions.

• Type: Conference
• Year: 2009
• Where: CMSB
• Authors: Lucia Napione, Daniele Manini, Francesca Cordero, András Horváth, Andrea Picco, Massimiliano De Pierro, Simona Pavan, Matteo Sereno, Andrea Veglio, Federico Bussolino, Gianfranco Balbo
• Keywords: Applied Computing, CMSB 2009, Signal Transduction, Signal Transduction Cascade, Signal Transduction Events