CiteULike is a free online bibliography manager. Register and you can start organising your references online.
Tags

A meta-analysis of cardiac electrophysiology computational models

by: S. A. Niederer, M. Fink, D. Noble, N. P. Smith
Experimental Physiology, Vol. 94, No. 5. (01 May 2009), pp. 486-495, doi:10.1113/expphysiol.2008.044610  Key: citeulike:4360627

Formatted Citation


Show HTML

Likes (beta)

This copy of the article hasn't been liked by anyone yet.

View FullText article


Abstract

Computational models of cardiac electrophysiology are exemplar demonstrations of the integration of multiple data sets into a consistent biophysical framework. These models encapsulate physiological understanding to provide quantitative predictions of function. The combination or extension of existing models within a common framework allows integrative phenomena in larger systems to be investigated. This methodology is now routinely applied, as demonstrated by the increasing number of studies which use or extend previously developed models. In this study, we present a meta-analysis of this model re-use for two leading models of cardiac electrophysiology in the form of parameter inheritance trees, a sensitivity analysis and a comparison of the functional significance of the sodium potassium pump for defining restitution curves. These results indicate that even though the models aim to represent the same physiological system, both the sources of parameter values and the function of equivalent components are significantly different.


saradtc's tags for this article

Citations (CiTO)

No CiTO relationships defined

X There are no reviews yet

X Find related articles from these CiteULike users

X Find related articles with these CiteULike tags

X Posting History


X Export records

Privacy Statement | Terms & Conditions
CiteULike organises scholarly (or academic) papers or literature and provides bibliographic (which means it makes bibliographies) for universities and higher education establishments. It helps undergraduates and postgraduates. People studying for PhDs or in postdoctoral (postdoc) positions. The service is similar in scope to EndNote or RefWorks or any other reference manager like BibTeX, but it is a social bookmarking service for scientists and humanities researchers.