A Priori Identifiability Analysis of Cardiovascular Models.

ABSTRACT: Model parameters, estimated from experimentally measured data, can provide insight into biological processes that are not experimentally measurable. Whether this optimized parameter set is a physiologically relevant complement to the experimentally measured data, however, depends on the optimized parameter set being unique, a model property known as a priori global identifiability. However, a priori identifiability analysis is not common practice in the biological world, due to the lack of easy-to-use tools. Here we present a program, Differential Algebra for Identifiability of Systems (DAISY), that facilitates identifiability analysis. We applied DAISY to several cardiovascular models: systemic arterial circulation (Windkessel, T-Tube) and cardiac muscle contraction (complex

SUBMITTER: Kirk JA 

PROVIDER: S-EPMC4696755 | biostudies-literature | 2013 Dec

REPOSITORIES: biostudies-literature