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An easy and efficient approach for testing identifiability.

Clemens Kreutz1,2

  • 1Center for Systems Biology (ZBSA), Habsburger Str. 49, University of Freiburg, 79104 Freiburg, Germany.

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|January 25, 2018
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Summary
This summary is machine-generated.

We present a fast method to test parameter identifiability in dynamical systems. This Identifiability-Test by Radial Penalization (ITRP) efficiently determines if model parameters can be uniquely estimated from data.

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Area of Science:

  • Mathematical modeling
  • Systems biology
  • Computational analysis

Background:

  • Assessing the unique estimation of parameters in dynamical systems is crucial for mathematical modeling.
  • Existing methods for parameter identifiability analysis are often computationally intensive and difficult to implement.

Purpose of the Study:

  • To introduce a novel, rapid approach for testing parameter identifiability in mathematical models.
  • To provide a computationally efficient and broadly applicable method for assessing model parameter uniqueness.

Main Methods:

  • Utilizes numerical optimization with a radial penalty to displace parameters.
  • Evaluates parameter uniqueness by checking for loss of agreement with data.
  • The Identifiability-Test by Radial Penalization (ITRP) is demonstrated on 11 ordinary differential equation (ODE) models.

Main Results:

  • The ITRP method allows for quick testing of parameter identifiability.
  • It effectively distinguishes between identifiable and non-identifiable parameters.
  • The approach is applicable to models where optimization-based parameter estimation is feasible, including systems biology models.

Conclusions:

  • The ITRP offers an efficient and accessible solution for parameter identifiability testing.
  • It can be readily integrated into existing modeling frameworks.
  • The method is available in the Data2Dynamics toolbox and as open-source code.