Stochastic modelling of signal transduction in olfactory neurons

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Authors

POKORA Ondřej

Year of publication 2010
Type Article in Proceedings
Conference 6th Summer School on Computational Biology
MU Faculty or unit

Faculty of Science

Citation
Web http://www.iba.muni.cz/summer-school2010/
Field General mathematics
Keywords sensory neurons;stochastic modelling;steady state
Description Several models of olfactory sensory neurons (concentration detectors, flux detectors) are investigated. Their behavior is described by stochastic processes of binding and activation. The models assume that the response, concentration of activated receptors, is determined by the signal, fixed log-concentration of odorant in perireceptor space. An approach used is based on stochastic variant of the law of mass action as a neuronal model. The statistical steady-state characteristics of the models are derived.
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