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Here is a citation for the database mentioned in the paper.
Subsequently the overlap of the two datasets was calculated using the database mentioned above.
The isobaric tags for relative and absolute quantitation (iTRAQ) data by Parker et al. were searched using the database mentioned above in order to generate information about total protein level changes (Supplementary Table S1).
The database also features a genome browser, which can be used to browse through the genome for representative features and also provides a visual representation of the associated genomic annotations available within the database mentioned above along with the conservation scores of lncRNAs.
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Meanwhile, not a single fund in the database mentions cigarettes or e-cigarettes as a focus area.
For more details about the databases mentioned and how they are matched, the reader is referred to Taştı (2009).
All the sequences were annotated according to their best BLAST hit against any of the databases mentioned above.
The databases mentioned in Table 2 were provided by the Swiss Federal Statistical Office (BfS) and the Swiss Federal Office for Spatial Development AREE).
Moreover, none of the databases mentioned above provide any biochemical information viz.
Almost all of the databases mentioned so far also contain information detailing interactions occurring between cells.
Through BLASTx against the databases mentioned above, the direction and region of CDS (coding sequences) were extracted from the sequences.
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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