PITHYA: High-Performance Parameter Synthesis for Biological Models
| Autoři | |
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| Rok publikování | 2017 |
| Druh | Další prezentace na konferencích |
| Fakulta / Pracoviště MU | |
| Citace | |
| Popis | Biological systems exhibit complex behaviour emerging from non-linear interactions among system components. A system can be specified in terms of an ODE (ordinary differential equations) model typically containing parameters which can significantly affect system behaviour. In general, it is difficult to obtain exact parameters values from experimental data. The number of parameters and their interdependence make the identification of parameters values a hard task. A common approach is to use parameter estimation from time-series data. Such data might be of low resolution or even unavailable. Instead of estimating parameters from data, an alternative approach is to specify global hypotheses on system behaviour in terms of temporal properties and to use parameter synthesis methods based on model checking, a verification technique proven by decades of use in computer science. We present a new high-performance tool Pithya that implements state-of-the-art parameter synthesis methods. For a given ODE model, it allows to visually explore model behaviour with respect to different parameter values. Moreover, Pithya automatically synthesises parameter values satisfying a given property. Such property can specify various behaviour constraints, e.g., maximal reachable concentration, time ordering of events, characteristics of steady states, presence of limit cycles, etc. |
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