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This is true for both models, as was also suggested by the mutant experiments since the clv1 phenotypes are slightly stronger than the crn phenotypes (Table 1).

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Expression of ZO-1 mRNA was significantly decreased in both ALF models, as was the level of ZO-1 protein.

In the heparanase-overexpressing mice, all aspects of immune cell recruitment and activation were significantly attenuated in both inflammation models, as was amyloid dispersion.

The former is the same for both models, as it is a function of the routing together with the demands placed on the network.

The results are presented in Table 7. Obviously both models, as a whole, were statistically significant (Chi-square P < 0.001).

For transparency we present both models as this approach is comparable to hierarchical regression analysis, so the absolute strength of the various paths depends on additional predictors in the model.

Bales were modelled both as being perfectly formed and as having a lower density close to their circular faces.

We have modeled both domains as being ohmic, i.e. their impedivities (z=rho) are only real valued, but z can be made complex by introducing a frequency dependence [34].

Biomass compositions in the published G. sulfurreducens model [ 22] were used to create the biomass demand reactions in both reconstructed Pelobacter models, as they are closely related to G. sulfurreducens.

In learner models that show both, as is necessary for negotiated learner modelling, attention needs to be given to how they can work together.

Importantly, even though BEL is well adapted to script biological network models as it is both human and machine-readable and requires little adjustments of linguistic tools, it is not the only language being used to represent biological knowledge.

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