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The both datasets are of different statistical characteristics, normalized and benchmarked in the recent literatures [ 17- 19].
Section "Results and discussion" lines 126-127 – Thexpressionon "Comparing the both datasets, …" might be inappropriate and might be even removed.
By comparing the minimum free energy of the common protein-coding RNAs and lincRNAs of the both datasets, the result showed that the minimum free energy of a large proportion of protein-coding RNAs was significantly higher than lincRNAs.
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For the southern part of the region both datasets show temperatures from 25° up to more than 40°C.
Although the first two principal components explain a significant amount of the variation in both datasets, only the Golub model performs well when cross-validated.
The ROCs for the predictions on both datasets are shown in Figure 2.
In addition, we also studied the credibility of the content captured from both datasets in the proposed temporal prediction models.
The richness values are the same in both datasets, but abscises may differ.
Figure 6 illustrates the memory usage comparison of the algorithms under both datasets.
Figure 4 plots the normalised RMSE (NRMSE) of the predictions for both datasets.
We expect that the most highly coexpressed genes will be the same within both datasets.
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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