Literature DB >> 2134490

Global identifiability of the parameters of nonlinear systems with specified inputs: a comparison of methods.

M J Chappell1, K R Godfrey, S Vajda.   

Abstract

The two methods available for analyzing the global structural identifiability of the parameters of a nonlinear system with a specified input function, the Taylor series approach and the similarity transformation approach, are compared and contrasted through application to three examples. It is shown that, as for linear systems, it is very difficult to predict which of the available methods will result in the least effort for a particular example. The role of modern symbolic manipulation packages in the analysis is assessed. The third example proves intractable using the similarity transformation approach as originally formulated, but the analysis is completed using a reformulation that exploits the polynominal form of the system equations in the example.

Mesh:

Year:  1990        PMID: 2134490     DOI: 10.1016/0025-5564(90)90055-4

Source DB:  PubMed          Journal:  Math Biosci        ISSN: 0025-5564            Impact factor:   2.144


  16 in total

1.  Optimal tumor targeting by antibodies: development of a mathematical model.

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2.  Examples of testing global identifiability of biological and biomedical models with the DAISY software.

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4.  Deterministic identifiability of population pharmacokinetic and pharmacokinetic-pharmacodynamic models.

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5.  On the identifiability of metabolic network models.

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Review 6.  Identifiability and indistinguishability of nonlinear pharmacokinetic models.

Authors:  K R Godfrey; M J Chapman; S Vajda
Journal:  J Pharmacokinet Biopharm       Date:  1994-06

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8.  What do we mean by identifiability in mixed effects models?

Authors:  Marc Lavielle; Leon Aarons
Journal:  J Pharmacokinet Pharmacodyn       Date:  2015-12-10       Impact factor: 2.745

9.  An approach for identifiability of population pharmacokinetic-pharmacodynamic models.

Authors:  V Shivva; J Korell; I G Tucker; S B Duffull
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2013-06-19

10.  Structural identifiability of systems biology models: a critical comparison of methods.

Authors:  Oana-Teodora Chis; Julio R Banga; Eva Balsa-Canto
Journal:  PLoS One       Date:  2011-11-22       Impact factor: 3.240

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