A compositional approach to performance modelling
A compositional approach to performance modelling
Information Processing Letters
Journal of Computational Physics
Probabilistic model checking of complex biological pathways
CMSB'06 Proceedings of the 2006 international conference on Computational Methods in Systems Biology
Analysis of signalling pathways using continuous time markov chains
Transactions on Computational Systems Biology VI
Symmetry reduction for probabilistic model checking
CAV'06 Proceedings of the 18th international conference on Computer Aided Verification
Algorithmic algebraic model checking i: challenges from systems biology
CAV'05 Proceedings of the 17th international conference on Computer Aided Verification
Transactions on Computational Systems Biology VII
PRISM: a tool for automatic verification of probabilistic systems
TACAS'06 Proceedings of the 12th international conference on Tools and Algorithms for the Construction and Analysis of Systems
Challenges for modeling and simulation methods in systems biology
Proceedings of the 38th conference on Winter simulation
Probabilistic model checking of complex biological pathways
Theoretical Computer Science
CMSB '08 Proceedings of the 6th International Conference on Computational Methods in Systems Biology
Modelling Intracellular Fate of FGF Receptors With BioAmbients
Electronic Notes in Theoretical Computer Science (ENTCS)
A stochastic pi calculus for concurrent objects
AB'07 Proceedings of the 2nd international conference on Algebraic biology
An automated translation from a narrative language for biological modelling into process algebra
CMSB'07 Proceedings of the 2007 international conference on Computational methods in systems biology
Abstract interpretation of cellular signalling networks
VMCAI'08 Proceedings of the 9th international conference on Verification, model checking, and abstract interpretation
Communications of the ACM
Predicting protein folding kinetics via temporal logic model checking
WABI'07 Proceedings of the 7th international conference on Algorithms in Bioinformatics
Probabilistic model checking of the PDGF signaling pathway
Transactions on Computational Systems Biology XIV
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Modelling of the dynamics of biochemical reaction networks typically proceeds by solving ordinary differential equations or stochastic simulation via the Gillespie algorithm. More recently, computational methods such as process algebra techniques have been successfully applied to the analysis of signalling pathways. One advantage of these is that they enable automatic verification of the models, via model checking, against qualitative and quantitative temporal logic specifications, for example, "what is the probability that the protein eventually degrades?". Such verification is exhaustive, that is, the analysis is carried out over all paths, producing exact quantitative measures. In this paper, we give an overview of the simulation, verification and differential equation approaches to modelling biochemical reaction networks. We discuss the advantages and disadvantages of the respective methods, using as an illustration a fragment of the FGF signalling pathway.