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Selected articles from each database were combined in one electronic library EndNote (Thomson Reuters, version X7).
The BesttrainBesttest and FasttrainFasttest prediction results for NCI database were combined in order to filter out possible false positive candidates.
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Search results from the different databases were combined in an endnote file and duplicates removed electronically and manually.
Results from all databases were combined in Endnote®, duplicates deleted and the results screened by title and abstract for suitability for the literature review.
Information from all databases were combined in one data matrix and Affymetrix probe sets were selected for the set of unique genes as described above resulting in 4,129 unique probe sets.
All cases defined by a specific Read or ICD 10 bleed code in either database were combined and duplicate events were excluded.
An SI-labeling technique, the HSQC-based metabolite chemical shift database, and heteronuclear multidimensional NMR spectroscopy were combined in a systematic method for simultaneously identifying a large number of metabolites.
The data obtained from both methods were combined in a database as described by López-Sánchez et al. (2009).
Extensively reviewed phenotypic data from all 10 cohorts were combined in a common database.
Information like fasta file headers, HMM result quality, tree position and manual, tree based classification of the sequences were combined in a sqlite database [http://www.sqlite.org] that was queried to created result statistics (see Methods S5).
Data extraction was done by a surgeon from each unit and data from the participating units were combined in a single database for the purpose of this study.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com