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Top five classification accuracies for the attributes and employed representations are summarized in Table 5.
Each of the 15 dyads, an explanation or simple example, and the corresponding diagram representations are summarized in Table 2.
The PD and breast cancer associations for both FFDM representations are summarized in Table 3 (raw) and Table 4 (processed).
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The procedures employed for learning and classification on the proposed representation are summarized in Algorithm 1 and Algorithm 2. In the learning stage, we initialize the weights corresponding to the elements of the training set such that the number of the samples within each class is taken into account.
The statistical representations of the results are summarized in Table 1 > -wrap-foot>.
The identified source statements are listed in Additional File 3, and simplified pairwise representations of the interactions are summarized in Table 4.
For reader's convenience, the representation methods under consideration are summarized in the following list.
Details regarding the treatment-specific representation of CanPIs and their IRD composition are summarized in Table 1.
The sequence changes between different primate species are summarized in a schematic representation of their phylogenetic relationship.
Known and predicted membrane-binding sites are summarized in Figure 1A.> -wrap-foot> Helical wheel representations for these helices are in Additional file 1: Figure S9.
The resulting distances to the optimum are summarized in Table 3 and a graphical representation of the fitted curves can be found in Figure S6.
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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