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A common principle for most of current methods for estimation of parameters in the models of biochemical networks is to minimize description between the observed and predicted quantities.
We fit the linear weighting parameters in the models of Figures 1I, 3A, 4A,C,D to maximize the estimation accuracy over a simulated ensemble of naturalistic motions.
The reactions are modeled over a 24 h diurnal cycle with inclusion of limited knowledge regarding the kinetic parameters in the models of the wild type and the mutant.
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Mutation rate per generation per locus is an important parameter in the models of population genetics.
The provided method is applied to identify all nonlinear parameters in the model of the nonlinear cantilever beam.
Neglecting one of these inherent parameters in the modeling of these systems can result in inaccurate predictions of their behaviors.
These 84 core samples are reused to calibrate the involved input parameters in the model of Xiao et al., separately.
By using the experimental data for N2O solubility, the parameters in the model of Weisenberger and Schumpe (Weisenberger and Schumpe, 1996) were refitted for aforementioned systems.
Thereafter, we study the setting of two uncertain parameters in the model of crack growth.
It can help us to decrease inaccuracies emerging from the ignored parameters in the modeling of real-life problems.
Including age-dependent parameters in the model (of unknown age dependency!) adds to the complexity – a simpler model with good explanatory power may be preferred.
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