PubMed 25705700
Referenced in: none
Automatically associated channels: TASK1
Title: Application of stochastic automata networks for creation of continuous time Markov chain models of voltage gating of gap junction channels.
Authors: Mindaugas Snipas, Henrikas Pranevicius, Mindaugas Pranevicius, Osvaldas Pranevicius, Nerijus Paulauskas, Feliksas F Bukauskas
Journal, date & volume: Biomed Res Int, 2015 , 2015, 936295
PubMed link: http://www.ncbi.nlm.nih.gov/pubmed/25705700
Abstract
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.