The applicability of these models is often restricted, by their inherent non-linearity, to simple beams.
However, the suitability of mouse models is often restricted by the fact that the effects of expression of an oncogene, or loss of a tumor suppressor, are exerted already at the embryonic stage and during tissue development, while in the vast majority of human cancers genetic alterations leading to cancer will occur in cells of adult tissues.
Yet the use of such implementation models is often restricted to the time frame after a research project closes.
This will often restrict the choice of the model to the one-box model.
Commercial developments often restrict the types of permissible businesses.
For those who do seek support, funding limitations often restrict the capacity of service providers.
Dorms often restrict what electrical appliances are allowed.
As a consequence their application to model organisms is often restricted to well characterized biological processes and pathways, and their effectiveness with poorly annotated species is relatively limited.
However, due to the overhead of handling complex geometries, mesh generation and visualization of results, algorithm developers often tend to consider only simple test models in simple geometries, often restricted to one or two spatial dimensions.
Large-scale models of cellular metabolism are becoming increasingly important for a variety of biotechnological applications, but are currently often restricted to a small number of model strains [ 27, 31].
