A comprehensive model of WNT/,B-catenin signaling | Interestingly, without this constraint we were not able to determine a parameter configuration matching the simulation results to in vitro measurements. |
A comprehensive model of WNT/,B-catenin signaling | Before we extensively discuss the simulation results , we first thoroughly validate the model and its current parametrization. |
A comprehensive model of WNT/,B-catenin signaling | The simulation results with the adapted model are depicted in Fig. |
Conclusion and Outlook | According to our simulation results , only a concisely regulated interplay between redox-dependent and self-induced auto-/paracrine WNT signaling can explain the nuclear fi-catenin dynamics observed experimentally during the initial phase of differentiation: |
Endogenous ROS signaling as potential trigger for ,B-catenin signaling | In summary, our simulation results suggest a twofold activation mechanism that drives the early differentiation process in human progenitor cells. |
Supporting Information | Simulation result for Raft/Receptor dynamics. |
Bow-tie architectures evolve when the goal is rank deficient | We also tested the sensitivity of the structure obtained to the evolutionary goal by comparing simulation results with different goals having the same rank. |
Bow-tie architectures evolve when the goal is rank deficient | We show simulation results of networks with L = 4 (5 layers of nodes) and 6 nodes in each layer (D = 6). |
Bow-tie architectures evolve when the goal is rank deficient | Each column in this figure shows simulation results for a different goal, and each row shows a different network layer. |
Discussion | We show simulation results of a simple nonlinear problem mimicking a 4-pixel retina. |
Discussion | (B) Typical example of simulation results . |
E E | We show simulation results when the goal consisted of a matrix of deficient rank (1 , 2 or 3) to which some level of noise was added (see Methods), so mathematically speaking goals had full rank, such that some of the eigenvalues were relatively small. |
Introduction | Generically, in fields as diverse as artificial neural networks [30] and evolution of biological networks, simulations result in highly connected networks with no bow-tie [31—37]. |
Supporting Information | Additional figures and simulation results as follows: 1.Parameter sensitivity test, 2. |
Comparison of analytical results with simulations data | 3(c)-(f) demonstrates that the analytical results slightly underestimate the simulation results to a small degree, especially if the mutated strain’s growth rate is high and R2 is close to K, but becomes more accurate as R2 increases and generally provides a good approximation. |
Comparison of analytical results with simulations data | Nevertheless, even in this case, Equation 7 accurately matches up with simulation results in this parameter range, although some inaccuracies arise for K = 1,000 (81 Fig). |
Supporting Information | Contains additional information on derivations, and further comparisons against simulation results (Mathematica NB format). |