A Boolean view separates platelet activatory and inhibitory signalling as verified by phosphorylation monitoring including threshold behaviour and integrin modulation.

Platelets are critical for haemostasis and blood clotting. However, since under normal circumstances blood should flow without clotting, its function is regulated via a complex interplay of activating and inhibiting signal transduction pathways. Understanding this network is crucial for treatment of cardiovascular and bleeding diseases. Detailed protein interaction and phosphorylation data are explored to establish a simplified Boolean model of the central platelet cascades. We implemented the model by means of CellNetAnalyzer and showed how different signalling events coalesce into a fully activated system state. Furthermore, we examined the networks' inherent threshold behaviour using the semi-quantitative modelling software SQUAD. Finally, predictions are verified monitoring phosphorylations which mark different activation phases as modelled. The model can also be applied to simulate different pharmacological conditions as they modify node activity (aspirin, clopidogrel, milrinon, iloprost, combination) and is available for further studies. It agrees well with observations. Activatory pathways are diversified to cope with complex environmental conditions. Platelet activation needs several activation steps to integrate over different network subsets, as they are formed by the interplay of activating kinases, calcium mobilization, and the inhibiting cAMP-PKA system. System stability analysis shows two phases: a sub-threshold behaviour, characterized by integration over different activatory and inhibitory conditions, and a beyond threshold phase, represented by competition and shutting down of counter-regulatory pathways. The integrin network and Akt-protein are critical for stable effector response. Dynamic threshold-analysis reveals a dependency of the relative activating input strength necessary to irreversibly engage the system from the absolute inhibitory signal strength.