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We used GEO datasets previously registered elsewhere [ 21] and combine these datasets with our original data.
To combine these datasets obtained from different microarray platforms, we performed the following pre-processing methods.
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We then combined these datasets by using the predicted zero flow duration from the regression model to determine appropriate 'zero' flow thresholds for the modelled discharge data, which varied spatially across the catchments examined.
We combined these datasets in a hydrologic model (the Water Evaluation And Planning system, WEAP) and modelled groundwater recharge from 2005 to 2016, permitting a characterization of the relationship between rainfall and groundwater recharge.
Combining these datasets allows for a more nuanced image of the existing transport flows in the study area.
Combining these datasets, the regions natural forests are estimated to store 216 ± 169Mg·ha−1 of carbon (mean ± 1 SD).
We combined these datasets to generate and validate multi-omic predictors of drug response.
By combining these datasets with mRNA expression, they highlighted expression changes correlating with mutations.
Combining these datasets and analyzing them to determine the genotypes expected (presuming homozygosity) for these lines from the sequence data, we can compare these expected genotypes to ALCHEMY calls.
When combined, these datasets may allow for the identification of potential weaknesses that can be used for development of new antimicrobials to reduce or eliminate C. jejuni and C. coli from the food chain.
As previous analyses have established that exenatide clearance is similar in patients with Type 2 diabetes and healthy volunteers [ 9] and the bioanalytical methodology was the same in every study, combining these datasets was justified.
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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