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Keywords
(23)
Arrhythmia
Cardiac Disease
Cellular Model
Differential Equation
Dynamic Model
Heuristic Algorithm
Ion Channel
Kinetic Model
Kinetic Theory
Kinetics
kolmogorov equation
Large Scale
Mathematical Model
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Partial Differential Equation
Potassium Channel
Protein Conformation
runge-kutta method
Ventricular Myocyte
Markov Model
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An Efficient Method for Modeling Kinetic Behavior of Channel Proteins in Cardiomyocytes
An Efficient Method for Modeling Kinetic Behavior of Channel Proteins in Cardiomyocytes,10.1109/TCBB.2011.84,IEEE/ACM Transactions on Computational Bi
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An Efficient Method for Modeling Kinetic Behavior of Channel Proteins in Cardiomyocytes
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Chong Wang
,
Peter Beyerlein
,
Heike Pospisil
,
Antje Krause
,
Chris Nugent
,
Werner Dubitzky
Characterization of the kinetic and conformational properties of channel proteins is a crucial element in the integrative study of congenital cardiac diseases. The proteins of the ion channels of cardiomyocytes represent an important family of biological components determining the physiology of the heart. Some computational studies aiming to understand the mechanisms of the ion channels of cardiomyocytes have concentrated on Markovian stochastic approaches. Mathematically, these approaches employ Chapman-Kolmogorov equations coupled with partial differential equations. As the scale and complexity of such subcellular and cellular models increases, the balance between efficiency and accuracy of algorithms becomes critical. We have developed a novel two-stage splitting algorithm to address efficiency and accuracy issues arising in such
modeling and simulation
scenarios. Numerical experiments were performed based on the incorporation of our newly developed conformational
kinetic model
for the rapid delayed rectifier
potassium channel
into the dynamic models of human ventricular myocytes. Our results show that the new algorithm significantly outperforms commonly adopted adaptive Runge-Kutta methods. Furthermore, our parallel simulations with coupled algorithms for multicellular cardiac tissue demonstrate a high linearity in the speedup of large-scale cardiac simulations.
Journal:
IEEE/ACM Transactions on Computational Biology and Bioinformatics - TCBB
, vol. 9, no. 1, pp. 40-51, 2012
DOI:
10.1109/TCBB.2011.84
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