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The same color dots represent terms which have similar biological functions.
The disconnected graphs represent terms that can be completely factored into a product of moments of lower order (cf. the middle diagram in Fig. 2b).
The edges and vertices represent terms (i.e. interactions) in the action and hence SDE, which are combined according to a set of rules that reproduces the perturbation expansion shown above.
In this figure, nodes with a check symbol represent terms included in the positive dataset.
The functional enrichment results are shown as a term relationship network, where nodes represent terms and edges show term relationships.
Smaller P-values represent terms that are more likely to be erroneously reported as significantly enriched using the standard method.
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Functional Group 15 represented terms linked with amino acid metabolism, suggesting an emphasis on protein synthesis.
Document vectors were generated as weighted superpositions of 32,000-dimensional binary-valued elemental term vectors representing terms they contain.
For the biological process category, response to salt stress and cadmium ion were the most highly represented terms (Fig. 1).
In the BP category, the two most represented terms are "transcription" (1.82 % +/− 0.09 %) and "regulation of transcription" (1.81 % +/− 0.17 %).
In the molecular function ontology class, the most represented terms describe catalytic (33.3%) and hydrolase activity (20.0%).
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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