000 03791nam a22005415i 4500
001 978-3-319-30030-6
003 DE-He213
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007 cr nn 008mamaa
008 160419s2016 gw | s |||| 0|eng d
020 _a9783319300306
_9978-3-319-30030-6
024 7 _a10.1007/978-3-319-30030-6
_2doi
050 4 _aQA71-90
072 7 _aPDE
_2bicssc
072 7 _aCOM014000
_2bisacsh
072 7 _aPDE
_2thema
082 0 4 _a004
_223
100 1 _aTveito, Aslak.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aComputing Characterizations of Drugs for Ion Channels and Receptors Using Markov Models
_h[electronic resource] /
_cby Aslak Tveito, Glenn T. Lines.
250 _a1st ed. 2016.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2016.
300 _aXVI, 261 p. 129 illus., 30 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Computational Science and Engineering,
_x1439-7358 ;
_v111
505 0 _aPreface -- 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 -- .
506 0 _aOpen Access
520 _aFlow 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.
650 0 _aComputer mathematics.
650 0 _aMedicine.
650 0 _aOptical data processing.
650 1 4 _aComputational Science and Engineering.
_0http://scigraph.springernature.com/things/product-market-codes/M14026
650 2 4 _aBiomedicine, general.
_0http://scigraph.springernature.com/things/product-market-codes/B0000X
650 2 4 _aComputer Imaging, Vision, Pattern Recognition and Graphics.
_0http://scigraph.springernature.com/things/product-market-codes/I22005
700 1 _aLines, Glenn T.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319300290
776 0 8 _iPrinted edition:
_z9783319300313
776 0 8 _iPrinted edition:
_z9783319807089
830 0 _aLecture Notes in Computational Science and Engineering,
_x1439-7358 ;
_v111
856 4 0 _uhttps://doi.org/10.1007/978-3-319-30030-6
912 _aZDB-2-SMA
912 _aZDB-2-SOB
999 _c525007
_d525005