Stochastic Modeling of Budding Yeast Cell Cycle

This report presents the definition, solution and validation of a stochastic model of the budding yeast cell cycle, based on Stochastic Petri Nets. A well-established deterministic model, based on ODEs, is considered as the basis for the stochastic modeling. A specific class of Stochastic Petri Nets is selected for building a stochastic version of the deterministic model, with applying the same abstractions of biological phenomena as the ones adopted in the deterministic model. We describe in the report the procedure followed in defining the SPN model from the deterministic one, a procedure that can be largely automated. The validation of the SPN model is conducted with respect to both the results provided by the deterministic one and the results available from wet-lab experiments. A very good match is obtained for the budding yeast wild type and for a variety of mutants that have been experimentally constructed in wet-labs. The results of the two models were compared against experimental data. We show that the stochasticity allows predicting characteristics that cannot be determined with the deterministic model. Moreover, we also show that the stochastic model can fine-tune the results of the deterministic model, enriching the breadth and the quality of the model.