With regard to the continuous autocrine signal, our findings are in line with a previous study of our group, where we used a simplified computational model to provide evidence for the self-induced autocrine/paracrine WNT signaling in hNPCs [44].

In addition we provide the first stochastic computational model of WNT/B-catenin signaling that combines membrane-related and intracellular processes, including lipid rafts/receptor dynamics as well as WNT- and ROS-dependent B-catenin activation.

The stochastic multilevel computational model we derive from our experimental measurements adds to the family of existing WNT models, addressing major biochemical and spatial aspects of WNT/beta-catenin signaling that have not been considered in existing models so far.

To summarize, based on our computational model , we demonstrated, that DVL may either act as amplifier or as direct inducer of canonical WNT signaling.

To explore the signaling mechanisms of both, the continuous activation pattern in untreated and in particular the early immediate response in raft-deficient cells, we perform a number of simulation studies based on a validated computational model of WNT signaling we will present in the following.

Computational modeling is increasingly applied to derive or test hypotheses, that in most cases arise from experimental data.

To evaluate, whether an interplay between ROS-induced and lipid raft dependent WNT/fi-catenin signaling can explain our experimental results we apply computational modeling .

Using computational models we show that neither channel noise nor a realistic cell morphology are responsible for the rate dependent shift in the phase response curve.

Furthermore, we address potential explanations for the observed transition using computational modeling .

Active conductances are thought to modulate the shape of the PRC, and therefore computational modeling [7, 47, 48] could be a powerful tool to dissect the ionic bases of the PRC.

PRCs computed for a highly detailed computational model of a Purkinje cell with synaptic activation in the dendritic tree.

The computational model .

(a) Diagram of the computational model colored by section name.

(c) The computational model parameters.