<div><p>Markov modeling provides an effective approach for modeling ion channel kinetics. There are several search algorithms for global fitting of macroscopic or single-channel currents across different experimental conditions. Here we present a particle swarm optimization(PSO)-based approach which, when used in combination with golden section search (GSS), can fit macroscopic voltage responses with a high degree of accuracy (errors within 1%) and reasonable amount of calculation time (less than 10 hours for 20 free parameters) on a desktop computer. We also describe a method for initial value estimation of the model parameters, which appears to favor identification of global optimum and can further reduce the computational cost. The PSO-G...
© 2019 Biophysical Society Mathematical models of ionic currents are used to study the electrophysio...
Cardiac electrophysiological computational models are often developed from previously published mode...
Cardiac electrophysiological computational models are often developed from previously published mode...
Markov modeling provides an effective approach for modeling ion channel kinetics. There are several ...
Markov modeling provides an effective approach for modeling ion channel kinetics. There are several ...
AbstractWe describe a maximum likelihood method for direct estimation of rate constants from macrosc...
Quantitative ion channel model evaluation requires the estimation of voltage dependent rate constant...
Computational models of ion channels represent the building blocks of conductance-based, biologicall...
AbstractFor single channel recordings, the maximum likelihood estimation (MLE) of kinetic rates and ...
In this work, we propose a methodology based on Monte Carlo Markov chains to explore the parameter s...
Markov models (MMs) represent a generalization of Hodgkin-Huxley models. They provide a versatile st...
Computational models of cardiac electrophysiology provided insights into arrhythmogenesis and paved ...
Estimation of the maximal ion channel conductances in Hodgkin-Huxley models from patch clamp data is...
AbstractHidden Markov modeling (HMM) provides an effective approach for modeling single channel kine...
Markov models of ion channel dynamics have evolved as experimental advances have improved our unders...
© 2019 Biophysical Society Mathematical models of ionic currents are used to study the electrophysio...
Cardiac electrophysiological computational models are often developed from previously published mode...
Cardiac electrophysiological computational models are often developed from previously published mode...
Markov modeling provides an effective approach for modeling ion channel kinetics. There are several ...
Markov modeling provides an effective approach for modeling ion channel kinetics. There are several ...
AbstractWe describe a maximum likelihood method for direct estimation of rate constants from macrosc...
Quantitative ion channel model evaluation requires the estimation of voltage dependent rate constant...
Computational models of ion channels represent the building blocks of conductance-based, biologicall...
AbstractFor single channel recordings, the maximum likelihood estimation (MLE) of kinetic rates and ...
In this work, we propose a methodology based on Monte Carlo Markov chains to explore the parameter s...
Markov models (MMs) represent a generalization of Hodgkin-Huxley models. They provide a versatile st...
Computational models of cardiac electrophysiology provided insights into arrhythmogenesis and paved ...
Estimation of the maximal ion channel conductances in Hodgkin-Huxley models from patch clamp data is...
AbstractHidden Markov modeling (HMM) provides an effective approach for modeling single channel kine...
Markov models of ion channel dynamics have evolved as experimental advances have improved our unders...
© 2019 Biophysical Society Mathematical models of ionic currents are used to study the electrophysio...
Cardiac electrophysiological computational models are often developed from previously published mode...
Cardiac electrophysiological computational models are often developed from previously published mode...