Stochastic Petri Net extension of a yeast cell cycle model.
This paper presents the definition, solution and validation of a stochastic model of the budding yeast cell cycle, based on Stochastic Petri Nets (SPN). A specific family of SPNs is selected for building a stochastic version of a well-established deterministic model. We describe the procedure followed in defining the SPN model from the deterministic ODE model, 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 experimental results available from literature. The SPN model catches the behavior of the wild type budding yeast cells and a variety of mutants. We show that the stochastic model matches some characteristics of budding yeast cells that cannot be found with the deterministic model. The SPN model fine-tunes the simulation results, enriching the breadth and the quality of its outcome.
Mura
Ivan
I
The Microsoft Research-University of Trento, Centre for Computational and Systems Biology, Piazza Manci 17, Povo-Trento I-38100, Italy. mura@cosbi.eu
Csikász-Nagy
Attila
A
D000465:Algorithms; D002453:Cell Cycle / Q000502:physiology*; D003198:Computer Simulation; D008954:Models, Biological; D004718:Saccharomycetales / Q000166:cytology*; D013269:Stochastic Processes; D049490:Systems Biology