Efficient stochastic simulation of reaction-diffusion processes via direct compilation.

Area of Science:

• Computational biology
• Biophysics
• Biochemical engineering

Background:

• Stochastic simulations are crucial for modeling biological systems where random fluctuations are significant.
• Existing tools often struggle with complex spatial heterogeneity and large system sizes, limiting their applicability.
• High-level descriptions of complex models are needed for efficient and accurate simulation.

Purpose of the Study:

• To introduce the Stochastic Simulator Compiler (SSC), a novel tool for exact stochastic simulations.
• To enable concise and readable high-level descriptions of complex, spatially heterogeneous systems.
• To achieve highly efficient simulations through direct native-code compilation.

Main Methods:

• Developing a compiler (SSC) that accepts high-level descriptions of simulation models.
• Implementing algorithms for both well-mixed and spatially heterogeneous systems.
• Utilizing direct native-code compilation for performance optimization.

Main Results:

• SSC is the first tool to support readable high-level descriptions for spatially heterogeneous simulation algorithms and complex geometries.
• SSC allows large systems to be expressed concisely.
• Direct native-code compilation results in very fast simulations.

Conclusions:

• SSC provides a powerful and efficient solution for exact stochastic simulations of complex biological systems.
• The tool's ability to handle spatial heterogeneity and large systems enhances its utility in computational biology.
• SSC facilitates faster and more accessible computational modeling of intricate biological processes.