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It initially constructs a neighbor-joining (NJ) tree using an arbitrary model (default is Jukes-Cantor [ 45] for nucleotides and JTT [ 14] for proteins) in order to get an initial base tree for comparison of models.
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Alternative trees for comparison were found based on RAxML searches (with gene partitions as detailed previously), but with the tree topology constrained to reflect the alternative hypothesis of choice (e.g., constrained for clade III monophyly).
Here, all boosting methods are based on decision tree for the comparison of performance.
All the likelihood based tree comparisons are provided [see Additional file 6].
That provides a base line for comparison to a doctor who has not treated you before.
g Base for comparison is never smoked.
g Base for comparison is current smoking.
(14) for monophyletic groups in the ARB base tree.
We chose to use 200 trees for the comparison with RF on the small dataset and 1000 trees for the comparison with BEAM on the big dataset.
This E2 subset tree was used for comparisons with the NSP3 tree to determine whether the trees shared similar topology.
Finally, look at the base of the tree for suckers.
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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