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pSSAlib: The partial-propensity stochastic chemical network simulator.

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pSSAlib is a new software library for simulating stochastic chemical kinetics. It enables the discovery of novel biological mechanisms, such as a stochastic switch in endosome conversion.

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Area of Science:

  • Computational Biology
  • Biophysics
  • Systems Biology

Background:

  • Biological systems rely on chemical reaction networks with inherently stochastic dynamics.
  • Accurate simulation of these stochastic processes is crucial for understanding cellular mechanisms.

Purpose of the Study:

  • To introduce pSSAlib, a software library implementing efficient partial-propensity methods for exact stochastic chemical kinetics simulation.
  • To provide a versatile tool for modeling complex biological systems, including those with time delays and spatiotemporal dynamics.

Main Methods:

  • Development and implementation of the pSSAlib software library.
  • Utilizing partial-propensity methods for precise simulation of stochastic chemical kinetics.
  • Importing models from Systems Biology Markup Language (SBML) and supporting time delays and reaction-diffusion systems.

Main Results:

  • pSSAlib offers a comprehensive and efficient solution for simulating stochastic chemical kinetics.
  • Application of pSSAlib to the endocytic pathway revealed a stochastic switch motif in early-to-late endosome conversion.
  • The library facilitates statistical analysis and supports various output formats for simulation results.

Conclusions:

  • pSSAlib is a powerful, open-source tool for advancing research in computational biology and systems biology.
  • The discovered stochastic switch provides new insights into the regulation of endosome trafficking.
  • pSSAlib is available as a command-line tool, developer API, and SBMLToolbox plug-in.