Parameter Synthesis and Robustness Analysis of Rule-Based Models
| Authors | |
|---|---|
| Year of publication | 2020 |
| Type | Article in Proceedings |
| Conference | 12th International Symposium on NASA Formal Methods, NFM 2020 |
| MU Faculty or unit | |
| Citation | |
| web | https://link.springer.com/chapter/10.1007/978-3-030-55754-6_3 |
| Doi | http://dx.doi.org/10.1007/978-3-030-55754-6_3 |
| Keywords | rule-based modelling; probabilistic models; parameter synthesis; robustness analysis |
| Description | We introduce the Quantitative Biochemical Space Language, a rule-based language for a compact modelling of probabilistic behaviour of complex parameter-dependent biological systems. Application of rules is governed by an associated parametrised rate function, expressing partially known information about the behaviour of the modelled system. The parameter values influence the behaviour of the model. We propose a formal verification-based method for the synthesis of parameter values (parameter synthesis) which ensure the behaviour of the modelled system satisfies a given PCTL property. In addition, we demonstrate how this method can be used for robustness analysis. |
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