Ion channel model reduction using manifold boundaries. Whittaker, D. G., Wang, J., Shuttleworth, J., Venkateshappa, R., Kemp, J. M., Claydon, T. W., & Mirams, G. R. Technical Report bioRxiv, March, 2022. Section: New Results Type: article![Ion channel model reduction using manifold boundaries [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Mathematical models of voltage-gated ion channels are used in basic research, industrial and clinical settings. These models range in complexity, but typically contain numerous variables representing the proportion of channels in a given state, and parameters describing the voltage-dependent rates of transition between states. An open problem is selecting the appropriate degree of complexity and structure for an ion channel model given data availability. Here, we simplify a model of the cardiac human Ether-à-go-go Related Gene (hERG) potassium ion channel, which carries cardiac IKr, using the manifold boundary approximation method (MBAM). The MBAM approximates high-dimensional model-output manifolds by reduced models describing their boundaries, resulting in models with fewer parameters (and often variables). We produced a series of models of reducing complexity starting from an established 5-state hERG model with 15 parameters. Models with up to 3 fewer states and 8 fewer parameters were shown to retain much of the predictive capability of the full model and were validated using experimental hERGla data collected in HEK293 cells at 37°C. The method provides a way to simplify complex models of ion channels that improves parameter identifiability and will aid in future model development.
@techreport{whittaker_ion_2022,
title = {Ion channel model reduction using manifold boundaries},
copyright = {© 2022, Posted by Cold Spring Harbor Laboratory. This pre-print is available under a Creative Commons License (Attribution 4.0 International), CC BY 4.0, as described at http://creativecommons.org/licenses/by/4.0/},
url = {https://www.biorxiv.org/content/10.1101/2022.03.11.483794v1},
abstract = {Mathematical models of voltage-gated ion channels are used in basic research, industrial and clinical settings. These models range in complexity, but typically contain numerous variables representing the proportion of channels in a given state, and parameters describing the voltage-dependent rates of transition between states. An open problem is selecting the appropriate degree of complexity and structure for an ion channel model given data availability. Here, we simplify a model of the cardiac human Ether-à-go-go Related Gene (hERG) potassium ion channel, which carries cardiac IKr, using the manifold boundary approximation method (MBAM). The MBAM approximates high-dimensional model-output manifolds by reduced models describing their boundaries, resulting in models with fewer parameters (and often variables). We produced a series of models of reducing complexity starting from an established 5-state hERG model with 15 parameters. Models with up to 3 fewer states and 8 fewer parameters were shown to retain much of the predictive capability of the full model and were validated using experimental hERGla data collected in HEK293 cells at 37°C. The method provides a way to simplify complex models of ion channels that improves parameter identifiability and will aid in future model development.},
language = {en},
urldate = {2022-03-17},
institution = {bioRxiv},
author = {Whittaker, Dominic G. and Wang, Jiahui and Shuttleworth, Joseph and Venkateshappa, Ravichandra and Kemp, Jacob M. and Claydon, Thomas W. and Mirams, Gary R.},
month = mar,
year = {2022},
doi = {10.1101/2022.03.11.483794},
note = {Section: New Results
Type: article},
keywords = {ion channels, model reduction, uses symengine, uses sympy},
pages = {2022.03.11.483794},
}
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