APPLICATION OF TECHNIQUE OF MONTE CARLO MONTE CARLO VIA MARKOV CHAIN ON MODEL OF MECHANISM CALCIUM INDUCED CLACIUM RELEASE IN NEURONS

Diego C. Estumano¹; Raphael C. Carvalho¹; Helcio R.B. Orlande¹; Marcelo J. Colaço¹; Eric Benk²; Jorge R.J²

¹ Department of Mechanical Engineering Federal University of Rio de Janeiro; ² Department of Biomedical Engineering, Florida International University

doi:10.20906/CPS/COB-2015-2657

Resumo

It is a challenge for some research find out some parameters present in the model mathematical. In this work is shown a Bayesian Technique called Monte Carlo via Markov Chain (MCMC) to estimate some parameters present in the model. This technique is applied in a model used to quantify the calcium concentration in neurons, the main goal of mathematical model is describe the mechanism of calcium induced calcium release (CICR). The first analysis was the sensitivity coefficient reduced, it was done to select which parameters could be estimated. The estimations of parameters was done using prior distribution Gaussian with the mean equal the parameters of reference and standard deviation equal 5, 7.5 and 10% of parameters of reference. Beyond the analysis of the prior distribution the other analysis is the error from measurement, for it was used simulated data with 1,5 and 10 % of calcium concentration present in the mathematical model.

Palavras-chave: Monte Carlo Markov Chain; CICR; Sensitivity Coefficient; estimation of parameters