Analysis of Signalling Pathways Using Continuous Time Markov Chains [chapter]

Muffy Calder, Vladislav Vyshemirsky, David Gilbert, Richard Orton
2006 Lecture Notes in Computer Science  
We describe a quantitative modelling and analysis approach for signal transduction networks. We illustrate the approach with an example, the RKIP inhibited ERK pathway [CSK + 03]. Our models are high level descriptions of continuous time Markov chains: proteins are modelled by synchronous processes and reactions by transitions. Concentrations are modelled by discrete, abstract quantities. The main advantage of our approach is that using a (continuous time) stochastic logic and the PRISM model
more » ... ecker, we can perform quantitative analysis such as what is the probability that if a concentration reaches a certain level, it will remain at that level thereafter? or how does varying a given reaction rate affect that probability? We also perform standard simulations and compare our results with a traditional ordinary differential equation model. An interesting result is that for the example pathway, only a small number of discrete data values is required to render the simulations practically indistinguishable.
doi:10.1007/11880646_3 fatcat:rd2ur64kmncqhano327w2yhag4