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We thank Andy Ball, Craig Meakin and Sophie Qin for improving the English text.
We wish to thank Raymond Jegat who built the testing devices, Thierry Papin who bred the mice and Shan Benson for improving the English text.
We are grateful to Dr. Bertrand Servin for improving the English text.
Special thanks to Tobey Curtis and the anonymous reviewers for helpful comments and improving the text.
Term clustering, by measuring the string similarities between terms, is known within the natural language processing community to be an effective method for improving the quality of texts and dictionaries.
We tested a strategy for improving the impact of HPV vaccination text message reminders through strategic wording.
In addition, we thank Mr. Oscar McCook as a medical writer for improving the clarity of the overall text.
The author also wishes to thank David T. McAuliffe, and his colleague Patrick J. Boner for their suggestions as to how to improve the text linguistically.
We have tried to improve the text of this section too, to make it clearer for the reader.
We are grateful for your comments, as they have improved the text and helped to understand an interdisciplinary problem more properly.
RESPONSE: We have improved the text in Abstract for clarity as shown below: Additionally, most of the published miRNA entity recognition methods are keyword based, f urther subjected to manual inspection for retrieval of relations.
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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