Difference between revisions of "Parameter identifiability example"
From BioUML platform
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| − | + | Identifiability analysis infers how well the model parameters are approximated by the amount and quality of experimental data [1,2]. | |
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| + | ==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''. | ||
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| + | Identifiability analysis can be run in two ways: | ||
| + | *to use a pre-created optimization document, double click on '''Parameter identifiability (optimization)'''; | ||
| + | * | ||
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| + | <h3>Parameter identifiability (optimization)</h3> | ||
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| + | <h3>Parameter identifiability (table)</h3> | ||
==References== | ==References== | ||
# 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. | # 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. | ||
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# Raue A, Becker V, Klingmüller U, Timmer J (2010) Identifiability and observability analysis for experimental design in nonlinear dynamical models. Chaos, 20(4):045105. | # 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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Revision as of 11:00, 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
- 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.
- Raue A, Becker V, Klingmüller U, Timmer J (2010) Identifiability and observability analysis for experimental design in nonlinear dynamical models. Chaos, 20(4):045105.
