Pharmacodynamic models for structural identifiability analysis
Parameter identifiability of fundamental pharmacodynamic models
... of structural identifiability, consider the two following biological ...formal structural identifiability analysis had not been performed then these two research projects would have ...
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Structural identifiability for mathematical pharmacology : models of myelosuppression
... four models are identifiable under certain simplifying ...the models and some empirical observations of parameter estimation ...structural identifiability. Some issues still exist with current ...
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Structural identifiability and indistinguishability in mixed effects models
... There are a several advantages of using mathematical modelling when devel- oping new pharmaceutical drugs. Firstly, modelling can be used to characterise the properties of a drug. With the use of modelling and ...
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Structural identifiability of large systems biology models
... numerical identifiability analysis. This analysis is tasked with spotting possible unidentifiable parameters and detecting both the number of totally correlated sets as well as which parameters ...
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Extending existing structural identifiability analysis methods to mixed effects models
... of structural identifiability for state-space models is expanded to cover mixed-effects state-space ...the structural identifiability of mixed-effects models are ...effects ...
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Structural identifiability and indistinguishability analyses of glucose insulin models
... the structural identifiability analyses of established and novel glucose-insulin models was performed, to determine whether the models are globally structurally identifiable with the ...
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Structural identifiability of equivalent circuit models for Li Ion batteries
... Abstract: Structural identifiability is a critical aspect of modelling that has been overlooked in the vast majority of Li-ion battery modelling ...ascertain structural identifiability are ...
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Structural identifiability in mixed effects models : two different approaches
... Abstract: Structural identifiability analysis is a theoretical concept that ascertains whether unknown model parameters can be uniquely determined for a given experimental ...Therefore, ...
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Structural identifiability analysis via symmetries of differential equations
... of models (for ex- ample nonlinear state space models) might be classified by the Lie algebras that act upon the observation in a trivial ...hence structural identifiability analysis ...
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Structural identifiability analyses of candidate models for in vitro Pitavastatin hepatic uptake
... 512996. models are proposed to characterise the uptake ...the models derived, as in most biomedical systems modelling, the model parameters have biological meaning and it is desired to establish whether it ...
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Structural Properties of Dynamic Systems Biology Models: Identifiability, Reachability, and Initial Conditions
... 3.5.2. Finding Solutions via Optimization An alternative, generally applicable way of answering this question is by formulating it as an optimization problem. In it, the decision variables are the system states, and the ...
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Identifiability and Minimality in Rational Models
... several models, such as Vectorial Autoregressive Moving Average (VARMA) models involving square matrices, Systems of Transfer Function Equations (STFE) with rectangular matrices, and ...series ...
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Input dependent structural identifiability of nonlinear systems
... namic models of biological systems. The three models were classified as structurally unidentifiable from an experiment with constant input, and structurally identifiable with time- varying ...these ...
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Identifiability in penalized function-on-function regression models
... Results Identifiability The estimation accuracy for ˆ Y (t) (not shown) is excellent across the board even for the very noisy settings, with a maximal relative integrated mean square error of ...Further ...
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Identifiability in Age/Period/Cohort Mortality Models
... thorough analysis of the identifiability is- sues in the chosen model, using the principles established in Section 4, to determine which features of the parameters are set by the data and which are set by ...
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MCMC, likelihood estimation and identifiability problems in DLM models
... 4 MCMC and Bayesian estimation An alternative to ML estimation is to use MCMC techniques within a Bayesian framework. The aim is to approximate the joint posterior distribution of the unknowns, states and parameters. ...
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On the description and identifiability analysis of experiments with mixtures
... regression models identified by a mixture ...retaining identifiability, strongly resembles the algebraic FGLM and Gr¨ obner walk algorithms Faug`ere et ...exemplifying analysis of two data sets is ...
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Identifiability Analysis of Inverse Problems in Biology
... HIV, Identifiability, Sensitivity-based analysis, Orthogonal method, Eigenvalue ...sensitivity-based identifiability analysis of parameters for mathematical models described by systems ...
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Analysis of Longitudinal Marginal Structural Models
... 6 Conclusion This paper presents two estimators for the causal parameter in a longitudinal marginal structural model: an IPTW or IPAW estimator and a treatment or action orthogonalized (one-step) estimator. ...
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Structural change and models of structural analysis: theories, principles and methods
... the analysis of structural change 12 ...empirical analysis of the investment ...dynamic analysis, in which the assumption that a constant proportion of input flows is allocated to investment ...
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