Exploring Parameter Space of Stochastic Biochemical Systems Using Quantitative Model Checking
| Authors | |
|---|---|
| Year of publication | 2013 |
| Type | Article in Proceedings |
| Conference | 25th International Conference, CAV 2013, Saint Petersburg, Russia, July 13-19, 2013. Proceedings |
| MU Faculty or unit | |
| Citation | |
| Web | http://link.springer.com/chapter/10.1007%2F978-3-642-39799-8_7 |
| Doi | http://dx.doi.org/10.1007/978-3-642-39799-8_7 |
| Field | Informatics |
| Keywords | continuous-time Markov chains; parameter exploration; model checking |
| Description | We propose an automated method for exploring kinetic parameters of stochastic biochemical systems. The main question addressed is how the validity of an a priori given hypothesis expressed as a temporal logic property depends on kinetic parameters. Our aim is to compute a landscape function that, for each parameter point from the inspected parameter space, returns the quantitative model checking result for the respective continuous time Markov chain. Since the parameter space is in principle dense, it is infeasible to compute the landscape function directly. Hence, we design an effective method that iteratively approximates the lower and upper bounds of the landscape function with respect to a given accuracy. To this end, we modify the standard uniformization technique and introduce an iterative parameter space decomposition. We also demonstrate our approach on two biologically motivated case studies. |
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