Fast adaptive uniformisation of the chemical master equation. Mateescu, M., Wolf, V., Didier, F., & Henzinger, T. IET Systems Biology, 2010.
doi  abstract   bibtex   
Within systems biology there is an increasing interest in the stochastic behaviour of biochemical reaction networks. An appropriate stochastic description is provided by the chemical master equationwhich represents a continuous-time Markov chain (CTMC). The uniformisation technique is an efficient method to compute probability distributions of a CTMC if the number of states is manageable. Howeverthe size of a CTMC that represents a biochemical reaction network is usually far beyond what is feasible. In this studythe authors present an on-the-fly variant of uniformisationwhere they improve the original algorithm at the cost of a small approximation error. By means of several examplesthe authors show that their approach is particularly well-suited for biochemical reaction networks. © 2010 © The Institution of Engineering and Technology.
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 title = {Fast adaptive uniformisation of the chemical master equation},
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 abstract = {Within systems biology there is an increasing interest in the stochastic behaviour of biochemical reaction networks. An appropriate stochastic description is provided by the chemical master equationwhich represents a continuous-time Markov chain (CTMC). The uniformisation technique is an efficient method to compute probability distributions of a CTMC if the number of states is manageable. Howeverthe size of a CTMC that represents a biochemical reaction network is usually far beyond what is feasible. In this studythe authors present an on-the-fly variant of uniformisationwhere they improve the original algorithm at the cost of a small approximation error. By means of several examplesthe authors show that their approach is particularly well-suited for biochemical reaction networks. © 2010 © The Institution of Engineering and Technology.},
 bibtype = {article},
 author = {Mateescu, M. and Wolf, V. and Didier, F. and Henzinger, T.A.},
 doi = {10.1049/iet-syb.2010.0005},
 journal = {IET Systems Biology},
 number = {6}
}

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