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Math Biosci ; 269: 10-6, 2015 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-26319118

RESUMO

The mathematical framework of the chemical master equation (CME) uses a Markov chain to model the biochemical reactions that are taking place within a biological cell. Computing the transient probability distribution of this Markov chain allows us to track the composition of molecules inside the cell over time, with important practical applications in a number of areas such as molecular biology or medicine. However the CME is typically difficult to solve, since the state space involved can be very large or even countably infinite. We present a novel way of using the stochastic simulation algorithm (SSA) to reduce the size of the finite state projection (FSP) method. Numerical experiments that demonstrate the effectiveness of the reduction are included.


Assuntos
Modelos Biológicos , Modelos Químicos , Algoritmos , Fenômenos Bioquímicos , Fenômenos Fisiológicos Celulares , Simulação por Computador , Cinética , Cadeias de Markov , Conceitos Matemáticos , Probabilidade , Processos Estocásticos
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