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Data publications are emerging as a way for researchers to write an additional article that provides an in-depth description of datasets behind research.
The experimental evaluation, including the description of datasets and experimental protocols, as well as a discussion of results, is presented in Section 4. We discuss Hidost's extension to other file formats and present a conceptual design for its application to office file formats OOXML and ODF in Section 5. Finally, Section 6 presents conclusions and outlines open questions for future work.
Description of datasets and a more extensive description of the applied methods can be found as supporting information (Discussion S1).
For all of the statistical analysis beyond the initial description of datasets, microarray data were normalized (Dataset S1) and a subset of the 12 microarray data (10 from melanoma cell lines and 2 from normal human melanocytes) was obtained by filtering to require each gene probe to have at least one observation in the expression intensity resulting in a 'present' call from all 12 samples.
A detailed description of datasets included in the meta-analysis is available in Table 1.
For vector comparisons, we constructed binary vectors (1 = observation, 0 = no observation) based on networks of functional interactions [ 31], genetic interactions (see description of datasets above), physical interactions (extracted from BioGRID [ 30]), and single gene-KO phenotypes [ 63].
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Table 4 Description of dataset Parameter Description Number of nodes 514 Number of edges 7153 Number of layers 16 Some keywords Neutrinos, detector, enhancements, anisotropy, point source.
Description of dataset and model for simulation and re-estimation.
Additional file 1: Description of dataset: Initial T 7 expression data in Table S1, S2 and S3.
Additional file 1: Norwegian (N.ref).and US cut-off values at 4, 6 and 12 months Description of dataset- Shows the recommended cut-off scores in Norway and US at 4, 6 and 12 months.
At a more specific level, these interprocess associations and functional descriptions of datasets can be used to uncover detailed biological responses in high-throughput data.
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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