Identification of parameter correlations for parameter estimation in dynamic biological models.

ABSTRACT:

Background

One of the challenging tasks in systems biology is parameter estimation in nonlinear dynamic models. A biological model usually contains a large number of correlated parameters leading to non-identifiability problems. Although many approaches have been developed to address both structural and practical non-identifiability problems, very few studies have been made to systematically investigate parameter correlations.

Results

In this study we present an approach that is able to identify both pairwise parameter correlations and higher order interrelationships among parameters in nonlinear dynamic models. Correlations are interpreted as surfaces in the subspaces of correlated parameters. Based on the correlation information obtained in this way both structural and pra

SUBMITTER: Li P 

PROVIDER: S-EPMC4015753 | biostudies-literature | 2013 Sep

REPOSITORIES: biostudies-literature