Stochastic Simulation (Gillespie Algorithm) Stochastic modeling based Discrete event simulation (iSimBioSys) Coments
1 nitialization: Initialize the number of molecules in the system, reactions constants, and random number generators Initialization: Initialize the number of molecules in the system for each species, model parameters and resources and random number generators The initialization steps are similar in both the algorithms
2 Monte Carlo Step: Generate random numbers to determine the next reaction to occur as well as the time interval. Event modeling and execution: The next reaction or molecular event is selected based on the functional logic hardwired in the simulator. For each process and its associated event, a random number is generated for the event execution time based on the first and second moment of the event holding time distribution computed by the stochastic model. In this step, Gillespie and other stochastic simulation algorithms employ a Monte Carlo step to determine next reaction event and time while in our approach, the next event selection and random execution time generation are computed differently.
3 Update: Increase the time step by the randomly generated time in step 1. Update the molecule count based on the reaction that occurred. Update: The global simulation clock is increased by the time-step computed in the previous step as the event holding time, The resource count of molecules are updated based on the last event stochiometry The temporal progression takes place in discrete time-steps based on the random event holding times computed in the previous step in our approach.
4 Iterate: Go back to Step 1 unless the number of reactants is zero or the simulation time has been exceeded. Iterate: Go back to Step 1 and repeat the process. In case a particular event cannot be executed because of resource conflicts, it is ignored and simulation proceeds without the update step The handling of reactions/events with resource conflicts/shortage is different in our approach
Table 2: Comparison of SSA and iSimBioSys modeling framework.