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The data obtained by all methods are in a good agreement.
All data regarding the DNA quantity measured by all methods are summarised in Table 1.
The estimates for positions and effects of QTL detected by all methods are fairly close to true parameter values.
Cooperative transcription factors predicted by all methods are closer and more clustered in the protein interaction network than expected by chance.
Interestingly, according to both measures the results produced by all methods are highly consistent, while the simulated annealing search appears to be only slightly more efficient than the hill climbing and genetic algorithm techniques.
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In Java, all methods are virtual by default and can be overridden by a derived class.
All methods are illustrated by worked examples.
However, all methods are limited by cross-reactions, particularly in New World ML, with antigens of Trypanosoma cruzi [ 6, 10].
For missing chunks, the error produced by all methods is so large, that none of them are recommended for this case.
For example, one important observation for the compounds showing high Vss prediction error (by all methods) is that the large majority of these compounds have a relatively extreme (very high or very low) Vss value, which seems to be the main reason for their large errors.
The selected genes by all methods were highly significant (P < 0.001).
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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