Abstract
Mathematical and computational models have become indispensable tools for integrating and interpreting heterogeneous biological data, understanding fundamental principles of biological system functions, generating reliable testable hypotheses, and identifying potential diagnostic markers and therapeutic targets. Thus, such tools are now routinely used in the theoretical and experimental systematic investigation of biological system dynamics. Here, we discuss model building as an essential part of the theoretical and experimental analysis of biomolecular network dynamics. Specifically, we describe a procedure for defining kinetic equations and parameters of biomolecular processes, and we illustrate the use of fractional activity functions for modeling gene expression regulation by single and multiple regulators. We further discuss the evaluation of model complexity and the selection of an optimal model based on information criteria. Finally, we discuss the critical roles of sensitivity, robustness analysis, and optimal experiment design in the model building cycle.
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Acknowledgments
This work was supported by the National Institutes of Health through grants from the National Institute of General Medical Sciences (R01-GM075152 and P50-GM076547), the National Technology Centers for Networks and Pathways (U54-RR022220), and the National Heart, Lung, and Blood Institute (K25-HL098807 to S.A.R).
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Ratushny, A.V., Ramsey, S.A., Aitchison, J.D. (2011). Mathematical Modeling of Biomolecular Network Dynamics. In: Cagney, G., Emili, A. (eds) Network Biology. Methods in Molecular Biology, vol 781. Humana Press. https://doi.org/10.1007/978-1-61779-276-2_21
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DOI: https://doi.org/10.1007/978-1-61779-276-2_21
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