Accounting for stochastic gating whilst estimating ion channel kinetics from voltage-clamp data

2909 

Contributed Abstract 

Poster 

Luca Del Core (1)

(1) University of Nottingham, Nottingham, UK

Luca Del Core  
University of Nottingham

Luca Del Core  
N/A

The heartbeat is coordinated by ion-channels in cell membranes that change their conformation, a process known as gating, allowing ions to pass through them. Mathematical models of cardiac ion channels can be defined as biochemical reactions describing the transitions between the ion channel configurations. Whole-cell voltage-clamp data allows us to calibrate the parameters of such mathematical models. However, standard approaches do not distinguish between stochastic noise and measurement errors, and the resulting estimates can be biased. To overcome these limitations, we propose a state-space model including a set of Itô-type stochastic differential equations describing ion channel gating, coupled with an Ohmic equation linking the noisy measurements to the ion channel configurations. Inference is based on an expectation-maximization algorithm. Synthetic studies show that our proposed method can infer the unknown parameters with a low degree of uncertainty and high predictive power. These results will improve models of ion channel dynamics by accounting for stochastic gating and measurement errors during fitting.

State-space models|expectation-maximization|parameter inference|ion channels|cardiac electrophysiology|uncertainty quantification

Uncertainty Quantification in Complex Systems Interest Group

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