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Users can also visualize ranking data by applying a thought multidimensional preference analysis.
Users can also visualize the quantified colony sizes as a heatmap or bubble plot.
In ProOpDB, users can also visualize operons in their genomic context and their nucleotide or amino acid sequences [ 11].
Users can also visualize the predicted output probabilities of being disordered for all residues when making a decision on threshold values for their purpose.
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The user can also visualize the protein-protein interaction graphs from STRING database in YDHS with one click from the menu.
User can also visualize and compare different tracks and hence analyze if there are similarities/dissimilarities between tracks.
In addition, the user can also visualize the ML-patch on the 3D-structure of the protein using the FirstGlance in Jmol applet.
You can also visualize your daily water levels to figure out if you are drinking enough.
You can also visualize a big red stop sign.
We can also visualize other benefits for this approach to tag recommendation as, for example, the exploration of the structure provided by its ontology for navigation on and visualization of the users' personomy.
Decision makers can also visualize potential load reductions under different water quality goals.
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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