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Delicious, once the data was normalized and reconfigured, had realistic potential to be an awesome blog content relevancy engine.
Data was normalized and analyzed using computer software (GeneSpring GX version 7.3).
Data was normalized and analyzed using computer software (GeneSpring GX 7.3).
Data was normalized and analyzed using Illumina Beadstudio 3.0 and GeneSpringGX 7.3.1 (Agilent Technologies).
Data was normalized and expressed as the % of FITC-peptide/DR1 complex remaining relative to the complex at t = 0, and fit to a single or double exponential model.
Data was normalized and detection calls were determined.
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Data were normalized and standardized.
Data were normalized and dead-time, random, scatter as well as attenuation corrections were applied.
PET data were normalized, and all appropriate corrections were applied for dead time, decay, randoms, and scatter.
Briefly, data were normalized, and ratio were next calculated (ERODActivity/Methylene blue, Fig. S3).
The data were normalized and averaged for graphical presentation in Figure 3B.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com