MomentClosure.jl: automated moment closure approximations in Julia

Area of Science:

• Computational biology
• Biochemical systems analysis
• Stochastic modeling

Background:

• Stochastic biochemical systems require accurate modeling of molecule number fluctuations.
• Exact analytical solutions to the chemical master equation are often unavailable.
• Monte Carlo simulations can be computationally expensive for large systems.

Purpose of the Study:

• To present MomentClosure.jl, a Julia package for automated moment equation derivation.
• To provide a flexible tool for applying various moment closure approximations.
• To enhance the modeling of stochastic biochemical systems in Julia.

Main Methods:

• Automated derivation of time-evolution equations for molecule number moments.
• Implementation of a wide range of moment closure approximations.
• Utilizes the Julia programming language for high performance.

Main Results:

• MomentClosure.jl successfully derives moment equations for diverse chemical reaction networks.
• The package facilitates the application of multiple moment closure approximations.
• Provides a computationally efficient alternative to Monte Carlo simulations.

Conclusions:

• MomentClosure.jl extends capabilities for modeling stochastic biochemical systems.
• It is particularly useful when exact solutions are unavailable or simulations are too costly.
• The package is freely accessible, promoting wider use in systems biology research.