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This suggests that within the network model there is covariation between these two features of the simulated ERP waveform, whereas in the data they are orthogonal.
In addition, our analysis suggests that, ultimately, the network model that one chooses to use requires a balance between re-learning known edges and discovering new potential interactions; the choice of which to emphasize depends of the goal of the analysis.
The conflicts discovered also suggest those parts of the network model (a priori generic) which should be adapted to the specificities of the cell line and phenotype.
The insight provided by the network model suggests that, at such a learning trial, the neural activity under-lying the decision making process may give rise to an above-chance correct response probability with high confidence, as in Figure 6B (see Appendix).
The network model thus suggests an important role of the different response time of PKR vs. PERK in the regulation of the downstream effectors of palmitate.
The network model recapitulates known resistance mechanisms to PI3K inhibitors and suggests other possibilities for resistance.
Strelioff [ 202] suggested a network model of the resistors and batteries to simulate the generation and distribution of the cochlear potentials, as shown in Figure 28.
Authors of [7] suggest an example network model for applying the proposed method and prove its effectiveness.
Übeyli suggested the combined neural network model for the classification using wavelet based features [ 12].
We suggest that network modeling analyses would be valuable in exploring how virus may spread from farm to farm.
For example the increasing use of SMP clusters (systems of multiprocessor compute nodes with very fast intra-node communications but relatively slow inter-node networks) suggest the use of hierarchical network models.
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