Cookies on this website
We use cookies to ensure that we give you the best experience on our website. If you click 'Continue' we will assume that you are happy to receive all cookies and you will not see this message again. Click 'Find out more' for information on how to change your cookie settings.

Since the development of the first mathematical cardiac cell model 50 years ago, computational modelling has become an increasingly powerful tool for the analysis of data and for the integration of information related to complex cardiac behaviour. Current models build on decades of iteration between experiment and theory, representing a collective understanding of cardiac function. All models, whether computational, experimental, or conceptual, are simplified representations of reality and, like tools in a toolbox, suitable for specific applications. Their range of applicability can be explored (and expanded) by iterative combination of 'wet' and 'dry' investigation, where experimental or clinical data are used to first build and then validate computational models (allowing integration of previous findings, quantitative assessment of conceptual models, and projection across relevant spatial and temporal scales), while computational simulations are utilized for plausibility assessment, hypotheses-generation, and prediction (thereby defining further experimental research targets). When implemented effectively, this combined wet/dry research approach can support the development of a more complete and cohesive understanding of integrated biological function. This review illustrates the utility of such an approach, based on recent examples of multi-scale studies of cardiac structure and mechano-electric function.

Original publication

DOI

10.1093/cvr/cvt003

Type

Journal article

Journal

Cardiovasc Res

Publication Date

15/03/2013

Volume

97

Pages

601 - 611

Keywords

Action Potentials, Animals, Calcium, Computer Simulation, ERG1 Potassium Channel, Ether-A-Go-Go Potassium Channels, Heart, Humans, Ion Channels, Models, Biological, Sinoatrial Node, Systems Biology, Ventricular Function, Left