Discrete stochastic simulation of cell signaling: comparison of computational tools.
Several stochastic simulation tools have been developed recently for cell signaling. A comparative evaluation of the stochastic simulation tools is needed to highlight the current state of the development. In our study, we have chosen to evaluate three stochastic simulation tools: Dizzy, Systems Biology Toolbox, and Copasi, using our own MATLAB implementation as a benchmark. The Gillespie stochastic simulation algorithm is used in all tests. With all the tools, we are able to simulate stochastically the behavior of the selected test case and to produce similar results as our own MATLAB implementation. However, it is not possible to use time-dependent inputs in stochastic simulations in Systems Biology Toolbox and Copasi. The present study is one of the first evaluations of stochastic simulation tools for realistic signal transduction pathways.
Manninen
Tiina
T
Inst. of Signal Process., Tampere Univ. of Technol, PO Box FI-33101 Tampere, Finland.
Mäkiraatikka
Eeva
E
Ylipää
Antti
A
Pettinen
Antti
A
Leinonen
Kalle
K
Linne
Marja-Linne
ML
D003198:Computer Simulation; D008954:Models, Biological; D011381:Programming Languages; D011493:Protein Kinase C / Q000378:metabolism*; D015398:Signal Transduction / Q000502:physiology*; D012984:Software; D012986:Software Validation; D013269:Stochastic Processes
D011493:Protein Kinase C