An iterative identification procedure for dynamic modeling of biochemical networks.

ABSTRACT:

Background

Mathematical models provide abstract representations of the information gained from experimental observations on the structure and function of a particular biological system. Conferring a predictive character on a given mathematical formulation often relies on determining a number of non-measurable parameters that largely condition the model's response. These parameters can be identified by fitting the model to experimental data. However, this fit can only be accomplished when identifiability can be guaranteed.

Results

We propose a novel iterative identification procedure for detecting and dealing with the lack of identifiability. The procedure involves the following steps: 1) performing a structural identifiability analysis to detect identifiable parameters; 2) g

SUBMITTER: Balsa-Canto E 

PROVIDER: S-EPMC2838808 | biostudies-literature | 2010 Feb

REPOSITORIES: biostudies-literature