Format

Send to

Choose Destination
Math Biosci. 2009 Dec;222(2):61-72. doi: 10.1016/j.mbs.2009.08.010. Epub 2009 Sep 6.

An algorithm for finding globally identifiable parameter combinations of nonlinear ODE models using Gröbner Bases.

Author information

1
UCLA, Department of Mathematics, Los Angeles, CA 90095, USA. nmeshkat@math.ucla.edu

Abstract

The parameter identifiability problem for dynamic system ODE models has been extensively studied. Nevertheless, except for linear ODE models, the question of establishing identifiable combinations of parameters when the model is unidentifiable has not received as much attention and the problem is not fully resolved for nonlinear ODEs. Identifiable combinations are useful, for example, for the reparameterization of an unidentifiable ODE model into an identifiable one. We extend an existing algorithm for finding globally identifiable parameters of nonlinear ODE models to generate the 'simplest' globally identifiable parameter combinations using Gröbner Bases. We also provide sufficient conditions for the method to work, demonstrate our algorithm and find associated identifiable reparameterizations for several linear and nonlinear unidentifiable biomodels.

PMID:
19735669
DOI:
10.1016/j.mbs.2009.08.010
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Elsevier Science
Loading ...
Support Center