The Next-Reaction-Method
This stochastic simulation method utilizes the algorithm developed by Gibson and Bruck [
Gibson00]. For each reaction a putative
stochastic reaction time is calculated and the reaction with the shortest reaction time will be realized. The set of
reactions is organized in a priority queue to allow for the efficient search for the fastest reaction. In addition,
by using a so-called dependency graph only those reaction times are recalculated in each step, that are dependent on
the reaction, which has been realized. This simulation method requires all the reactions to be irreversible.
However, COPASI provides a tool, that converts all reversible reactions into irreversible ones. Because the
algorithm internally works on discrete particle numbers rather than concentrations, the particle numbers in the
system must not exceed a value of $2^{64}-1$ which is approximately $1.84 \cdot 10^{19}$.
The current implementation of the Next Reaction Method is very inefficient when the model contains assignment rules,
which leads to extended calculation times.
There is a restriction regarding global quantities: If a differential equation is provided for a global quantity
(the quantity is of type "ode") the model cannot be simulated stochastically with the current version of
COPASI. If the global quantity is of type "assignment" stochastic simulation is possible but not as
efficient as for models without assignments. No restrictions apply for "fixed" global quantities.
Options for the Next-Reaction-Method
- Max Internal Steps
- This parameter is a positive integer value specifying the maximal number of internal steps the integrator is
allowed to take before the next desired reporting time. The default value is '1000000'.
- Subtype
- This parameter is ignored in the current version of COPASI.
- Use Random Seed
- This flag can be '0' or '1' and determines if the user-defined random seed should be used for the
calculation. The default is '0' meaning that the random seed is set to a random value before each run and
consecutively calculated trajectories will be different. If the value of this flag is set to '1', the
user-defined random seed will be used and each calculated trajectory will be the same for the same value of the
given random seed.
- Random Seed
- This unsigned integer is used as random seed in the calculations, if the flag Use Random Seed is set to '1'.
The default value is '1'.
The Direct-Method
This stochastic simulation method implements the Gillespie's direct method as described in [Gillespie76].
Options for the Direct-Method
- Max Internal Steps
- This parameter is a positive integer value specifying the maximal number of internal steps the integrator is
allowed to take before the next desired reporting time. The default value is '1000000'.
- Use Random Seed
- This flag can be '0' or '1' and determines if the user-defined random seed should be used for the
calculation. The default is '0' meaning that the random seed is set to a random value before each run and
consecutively calculated trajectories will be different. If the value of this flag is set to '1', the
user-defined random seed will be used and each calculated trajectory will be the same for the same value of the
given random seed.
- Random Seed
- This unsigned integer is used as random seed in the calculations, if the flag Use Random Seed is set to '1'.
The default value is '1'.
The τ-leap Method
This stochastic simulation method implements the τ-leap method as described in [Gillespie01]
Options for the τ-leap Method
- Max Internal Steps
- This parameter is a positive integer value specifying the maximal number of internal steps the integrator is
allowed to take before the next desired reporting time. The default value is '10000'.
- Use Random Seed
- This flag can be '0' or '1' and determines if the user-defined random seed should be used for the
calculation. The default is '0' meaning that the random seed is set to a random value before each run and
consecutively calculated trajectories will be different. If the value of this flag is set to '1', the
user-defined random seed will be used and each calculated trajectory will be the same for the same value of the
given random seed.
- Random Seed
- This unsigned integer is used as random seed in the calculations, if the flag Use Random Seed is set to '1'.
The default value is '1'.
The Adaptive SSA/τ-leap Method
This stochastic simulation method implements the Adaptive SSA/τ-leap Method as described in [Cao07]
Options for the Adaptive SSA/τ-leap Method
- Max Internal Steps
- This parameter is a positive integer value specifying the maximal number of internal steps the integrator is
allowed to take before the next desired reporting time. The default value is '10000000'.
- Use Random Seed
- This flag can be '0' or '1' and determines if the user-defined random seed should be used for the
calculation. The default is '0' meaning that the random seed is set to a random value before each run and
consecutively calculated trajectories will be different. If the value of this flag is set to '1', the
user-defined random seed will be used and each calculated trajectory will be the same for the same value of the
given random seed.
- Random Seed
- This unsigned integer is used as random seed in the calculations, if the flag Use Random Seed is set to '1'.
The default value is '1'.
