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The modeling framework should be semantically rich enough to work as a referential model and be semantically interpretable by end-users, i.e., the complexity of the model should be reasonable.
Overall, the analysis demonstrates that the image-based modeling framework should be used in conjunction with sophisticated data-mining tools for identification of microstructure property correlations in polycrystalline metals provided a statistically relevant number of grains are accommodated in the models.
In addition to asymmetric experimental design matrices, the modeling framework should cope, for instance, with, non-normal fitness value distributions and non-random missing value patterns.
Briefly, in analogy with the triplet model results from Pfister et al. 2006, we argue that our modeling framework should apply to those brain regions as well.
Further investigation would be required to fully understand the regulatory processes at work in this pathway for A. baylyi and extension of the modeling framework should be conducted to account for regulatory processes within the model.
Moreover, a modeling framework should be sufficiently versatile to span the whole diversity of neuron types by tuning a restricted number of parameters, avoiding the need of a new model for each class of neuron.
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The purpose of the model will condition the selection of the modeling framework and the information that should be included in the model.
It is concluded that a modeling framework such as the one presented should be used to generate a design protocol for reel-installed pipelines.
This new framework should now allow modeling and construction of T7 RNAP expression constructs that expand the utility of this enzyme for driving a variety of synthetic circuits and constructs.
In the next subsection we introduce two benchmark models, for the univariate and multivariate modeling framework.
The above probabilistic modeling framework that incorporates multiple motif models can be viewed as an extension of a framework proposed in [42].
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