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28 31 In the case of otelixizumab (non-FcR-binding anti-CD3), experience from murine models was combined with limited human data to arrive at a dose.
Each of the gene expression models was combined with the clinical model (Model A) additively to develop two clinical and gene expression models (D = A + C and E = A + D).
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After this, DNA and the VP4/VP5 models were combined to generate a filament model.
Resulting process models are combined to predict environmental concentrations (and related biological exposures) of anthropogenic and natural organic compounds.
The cost models are combined with high-level statistics collected from an actual execution to provide low-overhead profiling information.
The two models are combined to produce the final model, which is compared with observations.
These models are combined and refined using successive model transformations, until code is generated.
Then, the individual models are combined to generate simulated data that is compared with experiments.
The probability values of the models were combined using four different consensus methods.
The outputs from NN models are combined by three different aggregation algorithms.
Stratified sampling and species abundance models were combined in this study.
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CEO of Professional Science Editing for Scientists @ prosciediting.com