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Autor(en): 
  • Aslak Tveito
  • Glenn T. Lines
  • Computing Characterizations of Drugs for Ion Channels and Receptors Using Markov Models 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  April 2016  
    Genre:  EDV / Informatik 
     
    B / Biomedical Research / Biomedicine, general / Computational Science and Engineering / Computer Imaging, Vision, Pattern Recognition and Graphics / Computer mathematics / Computer Vision / Image processing
    ISBN:  9783319300290 
    EAN-Code: 
    9783319300290 
    Verlag:  Springer EN 
    Einband:  Gebunden  
    Sprache:  English  
    Serie:  #111 - Lecture Notes in Computational Science and Engineering  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Gewicht:  5561 gr 
    Seiten:  261 
    Illustration:  XVI, 261 p. 129 illus., 30 illus. in color., farbige Illustrationen, schwarz-weiss Illustrationen 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    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.

      



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