It is true that globally, the set of local simple models represent a complex model for intensity distribution modeling.
A simple model representing the interaction between these findings predicts that the EGO/TORC1 complex regulates the RTG transcriptional response, which in turn promotes ATP production in the mitochondria.
We emphasized that comparison of output model results to input is essential in knowing to what degree a simple model represents electrojet activity.
Here, we quantify the degree to which the simple model represented the data using standard statistical methods (see, e.g., Press et al. 1992).
The simple model represents the overall dynamics of the disease progression, including so-called acute pulmonary exacerbations, quite well, but of course does not provide much detail regarding the specific processes underlying the disease.
This simple model represents all of the experiments very well, indicating that the elastic anisotropy stems from the rolling-induced microstructure and, for the dual-phase steels, the presence of the second, reinforcing phase.
The simplest model represents the dissimilarity between two sounds and, averaged across the participants' ratings, by an Euclidean distance in a geometrical space with dimensions: (A1).
Neural networks are simple mathematical models representing a brain-like system.
The availability of different classes of drugs for chronic viral infections with differing targets within the relatively simple life cycle of these viruses has resulted in the development of simple semi-mechanistic models representing the life cycle of pathogens and/or their location in the host.
To understand the design principle behind this feed-back/feed-forward system we constructed two simple in silico models representing PCN interactions with PXR and its target gene CYP3A1 (Figure 6a), and LCA interactions with PXR, FXR and VDR, and their target genes CYP3A1, Fibrinogen B and CYP24 respectively (Figure 6b).
