TY - JOUR
T1 - Application of stochastic automata networks for creation of continuous time markov chain models of voltage gating of gap junction channels
AU - Snipas, Mindaugas
AU - Pranevicius, Henrikas
AU - Pranevicius, Mindaugas
AU - Pranevicius, Osvaldas
AU - Paulauskas, Nerijus
AU - Bukauskas, Feliksas F.
N1 - Publisher Copyright:
© 2015 Mindaugas Snipas et al.
PY - 2015
Y1 - 2015
N2 - The primary goal of this work was to study advantages of numerical methods used for the creation of continuous time Markov chain models (CTMC) of voltage gating of gap junction (GJ) channels composed of connexin protein. This task was accomplished by describing gating of GJs using the formalism of the stochastic automata networks (SANs), which allowed for very efficient building and storing of infinitesimal generator of the CTMC that allowed to produce matrices of the models containing a distinct block structure. All of that allowed us to develop efficient numerical methods for a steady-state solution of CTMC models. This allowed us to accelerate CPU time, which is necessary to solve CTMC models, ∼20 times.
AB - The primary goal of this work was to study advantages of numerical methods used for the creation of continuous time Markov chain models (CTMC) of voltage gating of gap junction (GJ) channels composed of connexin protein. This task was accomplished by describing gating of GJs using the formalism of the stochastic automata networks (SANs), which allowed for very efficient building and storing of infinitesimal generator of the CTMC that allowed to produce matrices of the models containing a distinct block structure. All of that allowed us to develop efficient numerical methods for a steady-state solution of CTMC models. This allowed us to accelerate CPU time, which is necessary to solve CTMC models, ∼20 times.
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U2 - 10.1155/2015/936295
DO - 10.1155/2015/936295
M3 - Article
C2 - 25705700
AN - SCOPUS:84924169435
SN - 2314-6133
VL - 2015
JO - BioMed Research International
JF - BioMed Research International
M1 - 936295
ER -