Flow of ions through voltage gated channels can be represented theoretically using stochastic differential equations where the gating mechanism is represented by a Markov model. The flow through a channel can be manipulated using various drugs, and the effect of a given drug can be reflected by changing the Markov model. These lecture notes provide an accessible introduction to the mathematical methods needed to deal with these models. They emphasize the use of numerical methods and provide sufficient details for the reader to implement the models and thereby study the effect of various drugs. Examples in the text include stochastic calcium release from internal storage systems in cells, as well as stochastic models of the transmembrane pot...
Abstract — Three reversible continuous time Markov chain models for ion channels based on the revers...
In this paper we provide two representations for stochastic ion channel kinetics, and compare the pe...
In this work, we propose a methodology based on Monte Carlo Markov chains to explore the parameter s...
Single channel dynamics can be modeled using stochastic differential equations, and the dynamics of ...
Mathematical models of the cardiac cell have started to include markovian representations of the ion...
Markov models (MMs) represent a generalization of Hodgkin-Huxley models. They provide a versatile st...
Computational Science and Engineering; Biomedicine general; Computer Imaging, Vision, Pattern Reco...
The behaviour of ion channels within cardiac and neuronal cells is intrinsically stochastic in natur...
The behaviour of ion channels within cardiac and neuronal cells is intrinsically stochastic in natur...
A Summary: Mathematical models of the cardiac cell have started to include markovian representations...
AbstractThe behaviour of ion channels within cardiac and neuronal cells is intrinsically stochastic ...
Ion channels are membrane proteins that open and close at random and play a vital role in the electr...
We consider the Bayesian analysis of mechanistic models describing the dynamic behavior of ligand-ga...
Ion channels are membrane proteins that open and close at random and play a vital role in the electr...
In this paper we provide two representations for stochastic ion channel kinetics, and compare the pe...
Abstract — Three reversible continuous time Markov chain models for ion channels based on the revers...
In this paper we provide two representations for stochastic ion channel kinetics, and compare the pe...
In this work, we propose a methodology based on Monte Carlo Markov chains to explore the parameter s...
Single channel dynamics can be modeled using stochastic differential equations, and the dynamics of ...
Mathematical models of the cardiac cell have started to include markovian representations of the ion...
Markov models (MMs) represent a generalization of Hodgkin-Huxley models. They provide a versatile st...
Computational Science and Engineering; Biomedicine general; Computer Imaging, Vision, Pattern Reco...
The behaviour of ion channels within cardiac and neuronal cells is intrinsically stochastic in natur...
The behaviour of ion channels within cardiac and neuronal cells is intrinsically stochastic in natur...
A Summary: Mathematical models of the cardiac cell have started to include markovian representations...
AbstractThe behaviour of ion channels within cardiac and neuronal cells is intrinsically stochastic ...
Ion channels are membrane proteins that open and close at random and play a vital role in the electr...
We consider the Bayesian analysis of mechanistic models describing the dynamic behavior of ligand-ga...
Ion channels are membrane proteins that open and close at random and play a vital role in the electr...
In this paper we provide two representations for stochastic ion channel kinetics, and compare the pe...
Abstract — Three reversible continuous time Markov chain models for ion channels based on the revers...
In this paper we provide two representations for stochastic ion channel kinetics, and compare the pe...
In this work, we propose a methodology based on Monte Carlo Markov chains to explore the parameter s...