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Mathematical modeling of biomolecular network dynamics.
Alexander V Ratushny1, Stephen A Ramsey, John D Aitchison
1Institute for Systems Biology, Seattle, WA, USA.
Methods in Molecular Biology (Clifton, N.J.)
|August 31, 2011
Summary
Mathematical modeling is crucial for analyzing biological systems. This study details model building for biomolecular network dynamics, including gene expression regulation and model selection.
Area of Science:
- Systems biology
- Computational biology
- Biophysics
Background:
- Mathematical and computational models are essential for biological data integration and hypothesis generation.
- These models are routinely used in theoretical and experimental investigations of biological system dynamics.
Purpose of the Study:
- To discuss model building as a key component in analyzing biomolecular network dynamics.
- To present a procedure for defining kinetic equations and parameters for biomolecular processes.
- To illustrate the application of fractional activity functions in modeling gene expression regulation.
Main Methods:
- Defining kinetic equations and parameters for biomolecular processes.
- Utilizing fractional activity functions to model gene expression regulation.
- Evaluating model complexity and selecting optimal models using information criteria.
- Performing sensitivity and robustness analyses, and employing optimal experiment design.
Main Results:
- A procedure for defining kinetic equations and parameters is described.
- Fractional activity functions are shown to be effective for modeling gene expression regulation.
- Model complexity evaluation and selection methods are discussed.
Conclusions:
- Model building is integral to the theoretical and experimental analysis of biomolecular network dynamics.
- Sensitivity, robustness analysis, and optimal experiment design are critical for refining biological models.
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