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Corrected pairwise divergences were calculated using the optimal models of nucleotide substitution determined by Modeltest for each gene separately.
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Then PAUP* was used to calculate the same likelihoods using the optimal model parameters estimated by GARLI.
Thus PAUP* was used to calculate likelihoods using the optimal model parameters estimated by RAxML for all of the tree topologies generated in RAxML and GARLI.
A tree constructed using the optimal model for this alignment (RtREV+I+G+F) agrees with the WAG tree.
Using the optimal model, we then accommodated topological uncertainty by removing the restriction of a fixed tree.
Three components were retained using the optimal model determination by the leave-one-out cross validation procedure and the minimum PRESS criteria (van der Voet's test).
The most likely phylogeny for each dataset was produced in Garli 2.0 (Genetic Algorithm for Rapid Likelihood Inference) [ 115], using the optimal model of evolution for each partition.
Maximum likelihood phylogenetic analyses were carried out using PHYML v2.4.4 [ 62] using the optimal model of sequence evolution identified with MODELGENERATOR v0.83 [ 46] and approximate likelihood ratio test support values [ 63].
Following optimisation of the k nearest neighbours and the Support Vector Machine algorithms using the training set, we tabulated the output obtained for the independent test set using the optimal model in terms of the number of samples correctly predicted and the number of samples incorrectly predicted.
Maximum-likelihood trees were constructed for each gene in PhyML 3.0 (http://www.atgc-montpellier.fr/phyml/) by using the optimal model for each alignment as identified by jModeltest 2 (TrN+I) and approximate-likelihood ratio test (aLRT) statistics computed for branch support (9, 10 ).
Then we use the optimal model to predict the testing sets and the performances are evaluated with accuracy, AUC and Cohen's kappa.
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