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SBaddon: high performance simulation for the Systems Biology Toolbox for MATLAB.

Henning Schmidt¹

¹Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Chalmers Science Park, SE-41288 Göteborg. henning@fcc.chalmers.se

Bioinformatics (Oxford, England)

|January 24, 2007

Summary

SBaddon enhances the Systems Biology Toolbox for MATLAB (SBtoolbox) with parameter estimation tools. It boosts simulation performance and adds optimization and identifiability analysis for systems biology research.

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Area of Science:

Systems Biology
Computational Biology
Bioinformatics

Background:

The Systems Biology Toolbox for MATLAB (SBtoolbox) is a widely used platform for systems biology modeling.
Parameter estimation is a critical but computationally intensive task in systems biology.

Purpose of the Study:

To introduce SBaddon, an extension for SBtoolbox, specifically designed to improve parameter estimation capabilities.
To enhance simulation performance and provide advanced analysis tools for SBtoolbox users.

Main Methods:

SBaddon automatically generates compiled simulation functions to accelerate computations.
The package incorporates improved optimization algorithms and sensitivity analysis techniques.
Basic numerical parameter identifiability analysis is included.

Main Results:

Significantly increased simulation performance compared to standard MATLAB ODE solvers.
Enhanced capabilities for parameter estimation and model analysis within the SBtoolbox environment.
Provided tools for forward parameter sensitivity and identifiability analysis.

Conclusions:

SBaddon offers valuable extensions for SBtoolbox, particularly for parameter estimation tasks.
The package improves computational efficiency and analytical power for systems biology modeling.
SBaddon is freely available for non-commercial use, promoting wider adoption in research.