Update docs/src/model_simulation/finite_state_projection_simulation.md

Co-authored-by: Sam Isaacson <[email protected]>

Author: TorkelE

docs/src/model_simulation/finite_state_projection_simulation.md

@@ -37,7 +37,7 @@ heatmap(osol(50.0); xguide = "Y", yguide = "X")
 
 Previously, we have shown how [*stochastic chemical kinetics*](@ref math_models_in_catalyst_sck_jumps) describe how chemical reaction network models can be [exactly simulated](@ref simulation_intro_jumps) (using e.g. [Gillespie's algorithm](https://en.wikipedia.org/wiki/Gillespie_algorithm)). We also described how the [SDE](@ref math_models_in_catalyst_cle_sdes) and [ODE](@ref math_models_in_catalyst_rre_odes) approaches were approximations of these jump simulations, and only valid for large copy numbers. To gain a good understanding of the system's time development, we typically have to carry out a large number of jump simulations. An alternative approach, however, is to instead simulate the *full probability distribution of the system*. This corresponds to the distribution from which these jump simulations are drawn.
 
-[*The chemical master equation*](https://en.wikipedia.org/wiki/Master_equation) (CME) describes the time development of this distribution[^1]. In fact, this equation is at the core of chemical reaction network kinetics, with all other approaches (such as ODE, SDE, and Jump simulations) being derived as various approximations of it. The CME is a system of ODEs, with one variable *for each possible state of the system*. Each of the ODE's variables describes (the rate of change in) the probability of the system being in that state. For a system with a single species $X$, the CME looks like
+[*The chemical master equation*](https://en.wikipedia.org/wiki/Master_equation) (CME) describes the time development of this probability distribution[^1], and is given by a (possibly infinite) coupled system of ODEs (with one ODE for each possible chemical state, i.e. number configuration, of the system). For a system with a single species $X$, the CME looks like
 ```math
 \begin{aligned}
 \frac{dp(x=0)}{dt} &= f_0(p(x=0), p(x=1), ...) \\