Subcellular models

The systems biology field has spawned a number of sophisticated software packages for simulating general intracellular processes. A number of these packages and their main features are described below.

An add-on package to GENESIS, Chemesis provides similar functionality to Kinetikit (see below), with added components to handle diffusion between well-mixed compartments, enabling the simulation of reaction-diffusion systems. Systems are constructed using the GENESIS scripting language.
The COmplex PAthway SImulator provides deterministic, stochastic and hybrid solutions for well-mixed reaction systems. Includes tools for parameter estimation and optimisation. It is platform independent.
Similar to Copasi. Model systems can be constructed via a scripting language, or graphically . A sophisticated graphical user interface is provided for both model construction and simulation.
This is for modelling biochemical systems. It translates the language of chemistry (reactions) to mathematics (matrices and differential equations) in a transparent way. It simulates the kinetics of systems of biochemical reactions and provides a number of tools to fit models to data, optimise any function of the model, perform metabolic control analysis and linear stability analysis.
This add-on package to GENESIS enables the simulation of well-mixed reaction systems, with deterministic, stochastic or adaptive deterministic-stochastic methods. Systems can be constructed graphically or via the GENESIS scripting language.
This simulator is aimed at modelling reaction-diffusion systems in three dimensions, at the level of individual molecules using stochastic algorithms for molecular diffusion and reaction . Reactions can only take place between freely diffusing molecules and membrane-bound receptors. Highly realistic spatial geometries are easily handled.
This is the Multiscale Object-Oriented Simulation Environment. It is the base and numerical core for large, detailed simulations in computational neuroscience and systems biology. MOOSE spans the range from single molecules to subcellular networks, from single cells to neuronal networks, and to still larger systems. It is backwards-compatible with GENESIS, and forward compatible with Python and XML-based model definition standards like SBML and MorphML.
This is a programming language for adding new components to NEURON. It enables the easy specification of reaction and diffusion systems, either through specification of the rate equations or the corresponding ODEs . In-built solution methods for deterministic systems are provided. Stochastic algorithms can be explicitly constructed from scratch using NMODL.
STEPS is a package for exact stochastic simulation of reaction-diffusion systems in arbitrarily complex 3D geometries. It is implemented in Python and the core simulation algorithm is an implementation of Gillespie's SSA (Box ), extended to deal with diffusion of molecules over the elements of a 3D tetrahedral mesh. Though developed for simulating detailed models of neuronal signalling pathways in dendrites and around synapses, it can be used for studying any biochemical pathway in which spatial gradients and morphology play a role.
This is aimed at stochastic modelling of individual molecules , and handles reactions between molecules in well-mixed compartments (no diffusion). Nearest-neighbour interactions between membrane-bound molecules are also possible.
This Virtual CELL simulator uses s to model deterministic reaction-diffusion systems in three dimensions. This enables detailed modelling of intracellular geometry and the concentration gradients of molecules through this space. It is provided as a Java application over the Internet by the National Resource for Cell Analysis and Modeling.