A local sensitivity analysis method for developing biological models with identifiable parameters: Application to cardiac ionic channel modelling

Sher, Anna A., Wang, Ken, Wathen, Andrew, Maybank, Philip John, Mirams, Gary R., Abramson, David, Noble, Denis and Gavaghan, David J. (2013) A local sensitivity analysis method for developing biological models with identifiable parameters: Application to cardiac ionic channel modelling. Future Generation Computer Systems-The International Journal of Grid Computing and Escience, 29 2: 591-598. doi:10.1016/j.future.2011.09.006


Author Sher, Anna A.
Wang, Ken
Wathen, Andrew
Maybank, Philip John
Mirams, Gary R.
Abramson, David
Noble, Denis
Gavaghan, David J.
Title A local sensitivity analysis method for developing biological models with identifiable parameters: Application to cardiac ionic channel modelling
Journal name Future Generation Computer Systems-The International Journal of Grid Computing and Escience   Check publisher's open access policy
ISSN 0167-739X
1872-7115
Publication date 2013-02-01
Year available 2013
Sub-type Article (original research)
DOI 10.1016/j.future.2011.09.006
Open Access Status Not Open Access
Volume 29
Issue 2
Start page 591
End page 598
Total pages 8
Place of publication Amsterdam, The Netherlands
Publisher Elsevier BV North-Holland
Language eng
Formatted abstract
Computational cardiac models provide important insights into the underlying mechanisms of heart function. Parameter estimation in these models is an ongoing challenge with many existing models being overparameterised. Sensitivity analysis presents a key tool for exploring the parameter identifiability. While existing methods provide insights into the significance of the parameters, they are unable to identify redundant parameters in an efficient manner. We present a new singular value decomposition based algorithm for determining parameter identifiability in cardiac models. Using this local sensitivity approach, we investigate the Ten Tusscher 2004 rapid inward rectifier potassium and the Mahajan 2008 rabbit L-type calcium currents in ventricular myocyte models. We identify non-significant and redundant parameters and improve the models by reducing them to minimum ones that are validated to have only identifiable parameters. The newly proposed approach provides a new method for model validation and evaluation of the predictive power of cardiac models
Keyword Local sensitivity analysis
Parameter identifiability
Overparameterisation
Cardiac modelling
Ionic channels
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Non HERDC
School of Information Technology and Electrical Engineering Publications
 
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Created: Wed, 23 Oct 2013, 01:36:49 EST by Ms Diana Cassidy on behalf of Research Computing Centre