An improved seven states Markov stochastic process model based on current channel structure information is proposed to elucidate and forecast Ca
v1.2
complex gating kinetic in the interactive cell environment regulated by multiple factors which plays a key role in the Ca
2+
metabolic cycle in functioning cells. Seven states are abstracted to present the limited conformational changes of Ca
v1.2
channel including VDI and CDI. Based on the Bayesian framework
the experiment data are then used to estimate the parameters of rate function between seven states via JAGS
which im
plements MCMC algorithm Gibbs sampler to sample the posterior distribution. The stochastic model is applied separately to stochastic PDEs profiling the Ca
2+
transient in the subspace and the changed electrophysiological behavior induced by the channel mutations G406R/G432N. The computational results show that the improved Ca
v1.2
Markov framework coincides well with the broad electrophysiological observations at the macroscopic level
and it also has a better predictability in the field of cardiomyocytes microstructure and channel genes pathology.
关键词
Keywords
references
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