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Additionally, the model makes testable predictions on pharmacological intervention to reactivate p53.
The model makes testable predictions concerning the duration and delay of the temporal episodes of V1 cell responses as well as their response variations that were caused by modulating feedback signals.
This minimal model makes testable predictions about the structural basis for directional, discrete and diversifying cell phenotype development and thus can guide the evaluation of real gene regulatory networks that govern differentiation.
Our model makes testable predictions on a variety of observable quantities.
This model makes testable predictions about where in parameter space real mitochondrial networks should fall to maintain mitochondrial function most successfully.
While the molecular details of this process remain unclear, this model makes testable prediction that for bivalent genes, MAE is established during lineage commitment events, such as ES cell differentiation.
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Nevertheless, our models make testable predictions and enable us to gain specific insights into gap gene regulation in C. albipunctata.
This quantitative model makes experimentally testable predictions.
This model makes two testable predictions.
Moreover, the model makes several testable predictions.
This model makes several testable predictions concerning (a) the encoding of object features in area AIP, (b) shifts in AIP activation during learning, and (c) the existence of an object-centered spatial representation for reach-to-grasp movements.
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