pSSAlib

pSSAlib simulates stochastic chemical kinetics using partial-propensity algorithms to model probabilistic biochemical reaction dynamics and spatiotemporal reaction-diffusion processes.

Key Features:

• Partial-Propensity Methods: Employs partial-propensity stochastic simulation algorithms to efficiently capture probabilistic reaction kinetics.
• Model Import and Compatibility: Supports SBML models for integration with existing systems biology models.
• Time Delays and Spatiotemporal Dynamics: Incorporates time delays and supports stochastic spatiotemporal reaction-diffusion systems.
• Statistical Analysis Tools: Provides tools for statistical analysis of simulation results to aid interpretation.
• Multiple Output Formats: Exports simulation data in multiple output formats for downstream analysis.
• Developer API and Plug-ins: Includes a developer API, a command-line interface, and an SBMLToolbox plug-in for integrations.

Scientific Applications:

• Endocytic Pathway Modeling: Models the endocytic pathway in eukaryotic cells and reveals a stochastic counterpart to the cut-out switch motif.

Methodology:

Simulations use partial-propensity stochastic simulation algorithms to simulate chemical kinetics, incorporating time delays and stochastic spatiotemporal reaction-diffusion dynamics.