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Exact(7)
Validation curves on both datasets are shown in Fig. 7.
The whole networks for both datasets are shown in Fig. 4.
The results of running the simulation using the contextual detection with the content detection for both datasets are shown in Figure 5.
The SNPs that are common to both datasets are shown in the shaded area.
The ROCs for the predictions on both datasets are shown in Figure 2.
The number of neighbor pairs for both datasets are shown in Supplementary Figure S1.
Similar(53)
The summary of both datasets is shown in Table 1.
The codon usage and RSCU of both datasets is shown.
The distributions of TGs in men and women in the full dataset are shown in Figs. 2 and 3; the prevalence of hypertriglyceridemia across both datasets is shown in Table 1.
The association between the presence of merged TF binding and strength of enhancement for both datasets was shown in Figure 5 (effects for individual TF are also shown in Additional file 2: Figure S7).
Model fit statistics for each of the models tested in both BWHHS and MRC datasets are shown in Table 1.
More suggestions(16)
both datasets are related
both leagues are shown
both halves are shown
both tracers are shown
both structures are shown
both compounds are shown
both efficiencies are shown
both datasets are summarised
both drugs are shown
both compositions are shown
both groups are shown
both datasets are studied
both parameters are shown
both conditions are shown
both CSSLs are shown
both cases are shown
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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