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＜電子ブック＞
Computing Characterizations of Drugs for Ion Channels and Receptors Using Markov Models / by Aslak Tveito, Glenn T. Lines
(Lecture Notes in Computational Science and Engineering. ISSN:21977100 ; 111)

版	1st ed. 2016.
出版者	(Cham : Springer International Publishing : Imprint: Springer)
出版年	2016
本文言語	英語
大きさ	XVI, 261 p. 129 illus., 30 illus. in color : online resource
著者標目	*Tveito, Aslak author Lines, Glenn T author SpringerLink (Online service)
件　名	LCSH:Mathematics -- Data processing  全ての件名で検索 LCSH:Medicine -- Research  全ての件名で検索 LCSH:Biology -- Research  全ての件名で検索 LCSH:Image processing -- Digital techniques  全ての件名で検索 LCSH:Computer vision FREE:Computational Science and Engineering FREE:Biomedical Research FREE:Computer Imaging, Vision, Pattern Recognition and Graphics
一般注記	Preface -- Background: Contents and Method -- One-dimensional calcium release -- Models of open and state blockers -- Two-dimensional calcium release -- Computing theoretical drugs in the two-dimensional case -- Generalized systems -- Calcium-induced calcium release -- Numerical release for CICR -- A prototypical model of an ion channel -- Inactivated ion channels -- A simple model of the sodium channel -- Mutations affecting the mean open time -- The burst mode -- Whole sale action potentials -- Open Access 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 potential. Well known Markov models are studied and a systematic approach to including the effect of mutations is presented. Lastly, the book shows how to derive the optimal properties of a theoretical model of a drug for a given mutation defined in terms of a Markov model HTTP:URL=https://doi.org/10.1007/978-3-319-30030-6

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