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To elucidate the phylogenetic positions of two mysterious Asian genera, Gastrophrynoides and Phrynella, and to better understand the trans-continental distributions of microhylid taxa, we performed molecular phylogenetic and dating analyses using the largest molecular dataset applied to these taxa to date.
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In this validation step, the method is examined using the datasets applied to ComPhy.
In this publication, we introduce new computational tools to analyze gene patterning for three spatial dimension datasets, applied to early Drosophila embryos.
The same approximation used for processing the experimental datasets applies to simulation data, then the same assumptions are considered.
After optimization of the neural networks in the training dataset, the final best neural network model, as measured by balanced accuracy in the training dataset, was applied to the testing dataset and evaluated.
For the training dataset, optimal results were obtained using Model 7. When the same analysis procedure of training dataset is applied to the test dataset (30 samples), similar results were obtained.
In the second step, the learning from this training dataset is applied to the prediction dataset and the classification is implemented.
Once the final model was selected, it was confirmed with the validation dataset and applied to the full dataset.
The predicting models built by CLR and ANN in modeling datasets were applied to testing datasets for generalization study.
Finally, the developed model based on the rat dataset was applied to the human data set to identify potential species differences in P-gp function.
The same procedure as used for the yeast dataset was applied to up-propagate the annotations.
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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