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In this context, we calculated the ratio of expressed genes per pathway (as defined by KEGG) for each gene expression sample.
DEG libraries were prepared using the Illumina gene expression sample prep kit.
Separately, 500 µl of the supernatant was supplemented either with 60 µl of previously washed anti-FLAG M2 agarose (Sigma) to be used as the total FLAG-tagged Slo3 expression sample, or with 60 µl Streptavidin agarose (Prozyme) to prepare Slo3 and β4 surface expression samples.
The first is based on a single expression sample (group).
These target metabolites might vary depending on the stage covered by the given gene expression sample.
The expression status was determined for each gene of every expression sample.
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The CK+ database (DB) is a set of facial expression samples posed by 123 people.
There's very little scope for the audience to apply their own context, or to reuse components into a reimagined expression (sampling being an exception, and again credit & payments are a challenge to say the least).
Where N is the number of expression samples, X is the expression level for gene X in ith sample, and Y is the expression level for gene Y in the ith sample (−1≤ r ≤1).
After removing gene expression samples with unknown survival information, 427 samples were used in our analysis.
This approach implicitly partitions the expression samples based on the modulator gene expression.
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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