Titlebook: Computing Characterizations of Drugs for Ion Channels and Receptors Using Markov Models; Aslak Tveito,Glenn T. Lines Book‘‘‘‘‘‘‘‘ 2016 The

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Action Potentials: Summing Up the Effect of Loads of Ion Channels,all parts of a cell. We started by studying the dynamics going on in a single dyad; see Fig.?2.1 The size of one dyad is less than 1/1,000?μm.[3] and we have been concerned with the concentration of calcium ions in this small volume. We have also studied the voltage dynamics in the vicinity of a sin

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Properties of Probability Density Functions,n be used to gain an understanding of calcium release. We will also show how the characteristics relate to the concepts already introduced and we will discuss how the characteristics vary as functions of the mutation severity index. Finally, we will show how the statistical characterizations can be

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1439-7358 ations is presented. Lastly, the book shows how to derive the optimal propertiesof a theoretical model of a drug for a given mutation defined in termsof a Markov model..978-3-319-80708-9978-3-319-30030-6Series ISSN 1439-7358 Series E-ISSN 2197-7100

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Didactical Problems with Decimals,l models often phrased in terms of differential equations. Our aim in these notes is to study such models and show how the effect of drugs can be optimized. More precisely, drugs are represented in terms of a set of parameters and we show how optimal drugs can be characterized by tuning the paramete

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Problems with Teaching Decimal Numbers, channels (LCCs). When these channels are open, calcium flows into a rather small space called the dyadic cleft (often simply referred to as the dyad), leading to a locally increased concentration of Ca. ions. This increased concentration leads to the opening of the ryanodine receptors (RyRs), which

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Didactical Problems with Decimals,ng release from internal storage to the dyad. We found that this model could be analyzed using Monte Carlo simulations or a system of deterministic partial differential equations giving the probability density functions of the open and the closed states. Furthermore, we found analytical solutions of

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Problems with Teaching Decimal Numbers,c models give results that are hard to interpret and it is therefore common to run many simulations and compute the average, and we have also seen that we can derive models governing the probability density functions. These are powerful tools that provide insight in the processes. In this chapter we

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https://doi.org/10.1007/0-306-47211-2hat the associated probability density functions are governed by 2 × 2 systems of partial differential equations. When a drug is added to the Markov model, an extra state is introduced associated with either the open or the closed state and we obtain a model for the probability density functions phr