Parameter sensitivity analysis in electrophysiological models using multivariable regression.

ABSTRACT: Computational models of electrical activity and calcium signaling in cardiac myocytes are important tools for understanding physiology. The sensitivity of these models to changes in parameters is often not well-understood, however, because parameter evaluation can be a time-consuming, tedious process. I demonstrate here what I believe is a novel method for rapidly determining how changes in parameters affect outputs. In three models of the ventricular action potential, parameters were randomized, repeated simulations were run, important outputs were calculated, and multivariable regression was performed on the collected results. Random parameters included both maximal rates of ion transport and gating variable characteristics. The procedure generated simplified, empirical models that predi

SUBMITTER: Sobie EA 

PROVIDER: S-EPMC2717232 | biostudies-literature | 2009 Feb

REPOSITORIES: biostudies-literature