A solver for the stochastic master equation applied to gene regulatory networks
Journal of Computational and Applied Mathematics
Hybrid method for the chemical master equation
Journal of Computational Physics
Inexact Uniformization Method for Computing Transient Distributions of Markov Chains
SIAM Journal on Scientific Computing
Spectral approximation of solutions to the chemical master equation
Journal of Computational and Applied Mathematics
Sliding Window Abstraction for Infinite Markov Chains
CAV '09 Proceedings of the 21st International Conference on Computer Aided Verification
Approximation of Event Probabilities in Noisy Cellular Processes
CMSB '09 Proceedings of the 7th International Conference on Computational Methods in Systems Biology
Fast Adaptive Uniformization of the Chemical Master Equation
HIBI '09 Proceedings of the 2009 International Workshop on High Performance Computational Systems Biology
An Adaptive Wavelet Method for the Chemical Master Equation
SIAM Journal on Scientific Computing
SHAVE: stochastic hybrid analysis of markov population models
Proceedings of the 14th international conference on Hybrid systems: computation and control
Communications of the ACM
Parameter identification for Markov models of biochemical reactions
CAV'11 Proceedings of the 23rd international conference on Computer aided verification
Parameter estimation for stochastic hybrid models of biochemical reaction networks
Proceedings of the 15th ACM international conference on Hybrid Systems: Computation and Control
Comparison of the mean-field approach and simulation in a peer-to-peer botnet case study
EPEW'11 Proceedings of the 8th European conference on Computer Performance Engineering
Dynamic bayesian networks: a factored model of probabilistic dynamics
ATVA'12 Proceedings of the 10th international conference on Automated Technology for Verification and Analysis
Quasi product form approximation for markov models of reaction networks
Transactions on Computational Systems Biology XIV
The Propagation Approach for Computing Biochemical Reaction Networks
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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We present a numerical approximation technique for the analysis of continuous-time Markov chains that describe networks of biochemical reactions and play an important role in the stochastic modeling of biological systems. Our approach is based on the construction of a stochastic hybrid model in which certain discrete random variables of the original Markov chain are approximated by continuous deterministic variables. We compute the solution of the stochastic hybrid model using a numerical algorithm that discretizes time and in each step performs a mutual update of the transient probability distribution of the discrete stochastic variables and the values of the continuous deterministic variables. We implemented the algorithm and we demonstrate its usefulness and efficiency on several case studies from systems biology.