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Related Experiment Videos

The SBML discrete stochastic models test suite.

Thomas W Evans1, Colin S Gillespie, Darren J Wilkinson

  • 1Department of Mathematical Sciences, University of Liverpool, Liverpool, L69 7ZL, UK.

Bioinformatics (Oxford, England)
|November 21, 2007
PubMed
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Checking stochastic simulators is challenging due to inherent randomness. A new test suite of validated stochastic models provides a reliable method for assessing simulator accuracy, aiding developers in ensuring correct mathematical modeling.

Area of Science:

  • Computational Mathematics
  • Scientific Computing

Background:

  • Stochastic simulation is crucial for mathematical modeling.
  • Verifying the accuracy of stochastic simulators is difficult because individual simulation runs produce different results.

Purpose of the Study:

  • To develop a reliable method for testing the correctness of stochastic simulators.
  • To provide a benchmark for evaluating the accuracy of stochastic simulation software.

Main Methods:

  • Creation of a test suite comprising stochastic models with pre-determined analytical or numerical solutions.
  • Utilizing these validated models to assess the performance of various stochastic simulators.

Main Results:

  • A comprehensive test suite for stochastic models has been developed.

Related Experiment Videos

  • This test suite allows for rigorous accuracy checks against known solutions.
  • The test suite is actively used by developers of stochastic simulation software.

    • Conclusions:

    • The developed test suite offers a robust solution for validating stochastic simulators.
    • It facilitates improved reliability and accuracy in mathematical modeling through simulation.