Calibrating functional parameters in the ion channel models of cardiac cells

• Autores: Matthew Plumlee, Roshan Joseph Vengazhiyil, Hui Yang
• Localización: Journal of the American Statistical Association, ISSN 0162-1459, Vol. 111, Nº 514, 2016, págs. 500-509
• Idioma: inglés
• DOI: 10.1080/01621459.2015.1119695
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• Resumen

  • Computational modeling is a popular tool to understand a diverse set of complex systems. The output from a computational model depends on a set of parameters that are unknown to the designer, but a modeler can estimate them by collecting physical data. In the described study of the ion channels of ventricular myocytes, the parameter of interest is a function as opposed to a scalar or a set of scalars. This article develops a new modeling strategy to nonparametrically study the functional parameter using Bayesian inference with Gaussian process prior distributions. A new sampling scheme is devised to address this unique problem.