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DOE OSTI · 1574756

Parameter Estimation and Uncertainty Quantification for Systems Biology Models

Mitra, Eshan David·Hlavacek, William Scott
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Abstract

Mathematical models can provide quantitative insights into immunoreceptor signaling, and other biological processes, but require parameterization and uncertainty quantification before reliable predictions become possible. We review currently available methods and software tools to address these problems. We consider gradient-based and gradient-free methods for point estimation of parameter values, and methods of profile likelihood, bootstrapping, and Bayesian inference for uncertainty quantification. We consider recent and potential future applications of these methods to systems-level modeling of immune-related phenomena.

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59 BASIC BIOLOGICAL SCIENCESbiological modelingimmune cell signaling

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BibTeXRIS

Mitra, Eshan David, Hlavacek, William Scott. 2019-11-06. Parameter Estimation and Uncertainty Quantification for Systems Biology Models. https://doi.org/10.1016/j.coisb.2019.10.006

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