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The other popular terms were then added as synonyms.
These selected terms were then manually grouped into appropriate classes for simplicity of presentation.
These source terms were then updated upon receipt of first chemical and textural analyses.
The concept map and the prescribed terms were then translated into Japanese in collaboration with the professor.
The most frequent class candidate terms were then manually defined in the chemical ontology via SMARTS expressions.
These terms were then used to build a PLS model as a scoring function to estimate the free energy of binding.
These key terms were then sought in the radiology reports of a separate sample of 20 subjects that we felt had undergone the Ertl procedure based on their radiology report alone as they were without viewable radiographs.
They conclude that kings X derived from the users of kings and exes settling in the same areas of the US the terms were then combined and shortened.
Statistically over-represented terms were then mapped to the GO directed acyclic graph.
MeSH terms were then used verbatim without any further tokenization; those that occurred in fewer than four documents were ignored.
The annotated KO terms were then compared against all human proteins as the background set for assessing if they are enriched or underrepresented.
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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