| Ամփոփում: | <br>Mathematical modelling of complex biological phenomena allows us to understand the contributions of different processes to observed behaviours. Many of these phenomena involve the
reaction and diffusion of molecules and so we use so-called reaction-diffusion models to describe them mathematically. Reaction-diffusion models are often subdivided into three types
(Hellander & Petzold, 2017): macroscopic, mesoscopic and microscopic. Models that describe
a system in terms of concentrations are termed macroscopic models. At the other end of the
spectrum we have microscopic models that describe a system by specifying the positions (and
often velocities) of each molecule. The middle ground between these two scales is covered by
mesoscopic models, in which stochasticity and some individual-level details are included without directly tracking the position of every single molecule. Macroscale models ignore crucial
details such as stochastic effects, while microscale models tend to be computationally intensive
(Osborne, Fletcher, Pitt-Francis, Maini, & Gavaghan, 2017; Van Liedekerke, Palm, Jagiella, &
Drasdo, 2015). Mesoscale models offer a good balance in that they include stochastic effects
without incurring enormous computational overheads. The frameworks of the chemical master equation (CME) and its spatial extension, the reaction-diffusion master equation (RDME)
(Isaacson, 2009, 2013; Van Kampen, 1992), provide mesoscopic models of reaction and diffusion. However, in the majority of these cases, models built in the CME/RDME framework are
analytically intractable and so model behaviours must be explored using stochastic simulation
algorithms.</br>
<br>StoSpa2 is a C++ software package for stochastic simulation of models constructed using the
CME and RDME frameworks. This software package allows for efficient simulations with a
user friendly interface, and it includes functionality for simulations on both static and growing
domains, and time-varying reaction rates.</br>
<br>The primary audience of StoSpa2 are researchers who wish to model a chemical or biological
system using the CME or RDME frameworks.</br>
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