Difference between revisions of "Parameter identifiability example"

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==Reproducing a test case in BioUML==
 
==Reproducing a test case in BioUML==
To reproduce a test case below in the [[BioUML]] workbench, go to the <b>Analyses</b> tab in the navigation pane and follow to ''analyses'' > ''Methods'' > ''Differential algebraic equations''. Identifiability analysis can be run in two ways:
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To reproduce a test case below in the [[BioUML]] workbench, go to the <b>Analyses</b> tab in the navigation pane and follow to ''analyses'' > ''Methods'' > ''Differential algebraic equations''.
 +
 
 +
Identifiability analysis can be run in two ways:
 
*to use a pre-created optimization document, double click on '''Parameter identifiability (optimization)''';
 
*to use a pre-created optimization document, double click on '''Parameter identifiability (optimization)''';
 
*
 
*

Revision as of 11:01, 16 March 2022

Identifiability analysis infers how well the model parameters are approximated by the amount and quality of experimental data [1,2].

Contents

Reproducing a test case in BioUML

To reproduce a test case below in the BioUML workbench, go to the Analyses tab in the navigation pane and follow to analyses > Methods > Differential algebraic equations.

Identifiability analysis can be run in two ways:

  • to use a pre-created optimization document, double click on Parameter identifiability (optimization);

Parameter identifiability (optimization)

Parameter identifiability (table)

References

  1. Raue A, Kreutz C, Maiwald T, Bachmann J, Schilling M, Klingmüller U, Timmer J (2009) Structural and practical identifiability analysis of partially observed dynamical models by exploiting the profile likelihood. Bioinformatics, 25(15):1923–1929.
  2. Raue A, Becker V, Klingmüller U, Timmer J (2010) Identifiability and observability analysis for experimental design in nonlinear dynamical models. Chaos, 20(4):045105.

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