Sentence examples for model networks to from inspiring English sources
We provide damage propagation analysis and an extensive statistical analysis of state spaces of these model networks to show that the change in their dynamical properties due to stabilizing selection for optimal phenotypes is minor.
In our work we used a set of widely adopted model networks to simulate the complexity of real-world situations.
To examine the fit of model networks to RIGs corresponding to a larger number of proteins, we analyze Data Set 2 (described in Section "Data Sets").
To check the significance of our results, we have subjected both the real and the model networks to a rewiring of the edges while i) keeping the degree distributions fixed while ignoring the directionality and ii) conserving the directionality so that the in- and out- degree distributions are kept fixed separately.
We also report the GDDA values when one compares an ER-DD query network with ER model networks to show how the method behaves for two closely related models (Fig. 4D).
It also provides the constraints on the architecture required to construct a model network to simulate mRNA production.
It is not sufficient to use a powerful decoder after the model network to achieve the required performance, instead of invariance being represented by the neurons themselves in the model of the ventral visual system.
As we were unable to reliably localize face-selective activation in the anterior temporal lobe in a sufficient number of subjects, we restricted our model network to OFA and FFA.
Have the authors effectively varied the state of excitation for example in the model network to gain insight into how level of excitation affects the critical mass of neurons required to sustain rhythmogenic function?
Thus, in addition to analyzing 1785 RIGs, we also analyzed 5×30×1785 = 267,750 model networks corresponding to the RIGs and compared them to the RIGs (see Section "Network Comparisons").
RIGs are compared to the corresponding model networks with respect to two graphlet-based local and five standard global network properties.
