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    Biological mechanism and identifiability of a class of stationary conductance model for Voltage-gated Ion channels


    Francis, Febe, García, Míriam R., Mason, Oliver and Middleton, Richard H. (2013) Biological mechanism and identifiability of a class of stationary conductance model for Voltage-gated Ion channels. Working Paper. Arxiv.

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    Official URL: http://arxiv.org/abs/1312.3991

    Abstract

    The physiology of voltage gated ion channels is complex and insights into their gating mechanism is incomplete. Their function is best represented by Markov models with relatively large number of distinct states that are connected by thermodynamically feasible transitions. On the other hand, popular models such as the one of Hodgkin and Huxley have empirical assumptions that are generally unrealistic. Experimental protocols often dictate the number of states in proposed Markov models, thus creating disagreements between various observations on the same channel. Here we aim to propose a limit to the minimum number of states required to model ion channels by employing a paradigm to define stationary conductance in a class of ion-channels. A simple expression is generated using concepts in elementary thermodynamics applied to protein conformational transitions. Further, it matches well many published channel current-voltage characteristics and parameters of the model are found to be identifiable and easily determined from usual experimental protocols.
    Item Type: Monograph (Working Paper)
    Keywords: Biological mechanism; identifiability; stationary conductance model; Voltage gated; Ion channels;
    Academic Unit: Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Faculty of Science and Engineering > Mathematics and Statistics
    Item ID: 6231
    Identification Number: arXiv:1312.3991
    Depositing User: Oliver Mason
    Date Deposited: 03 Jul 2015 14:21
    Publisher: Arxiv
    Funders: Science Foundation Ireland (SFI)
    URI: https://mu.eprints-hosting.org/id/eprint/6231
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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