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The best cutoff values were identified using the maximal value of Youden's index (sensitivity + specificity − 1) as the criterion.
The cutoff values were identified using the negative controls provided in the kit (using the formula, 4X negative control).
The ratios of invariant to variable mutations at non-synonymous and synonymous sites were calculated; significant differences between these values were identified using a G-test.
One-way analysis of variance was performed, and when the significance (p < 0.05) was determined, the differences of the mean values were identified using Duncan's multiple range tests.
For the independent predictors of AKI, adequate cutoff values were identified using a receiver operating characteristic (ROC) curve, and the area under the curve (AUC) was used to determine the accuracy of the model.
Thus, to further test the relationship between tumors and metastases, ICC values were identified using a compendium of 298 different gene expression signatures/modules [ 12], where each module is a summary measure of tens to hundreds of genes.
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The optimal product realization process alternative and its parameter values are identified using a multi-level optimization method.
q-valued candidate genes were identified using a q-value(minimum value of false discover rate)of <0.001.
The values of 45%and65%65 % were identified using a small dataset including thiopeptide, thermoacidophisin, cytolysin, and hakacin producers.
Outliers were identified on the basis of their standardized residual values, while influential cases were identified using their predicted values, Cook's distance statistics, leverage values, and their DFBeta values.
GO terms differentially represented in HS (lower MFA) and LS (high MFA) wood (P-values ≤ 0.05) were identified using the "library comparison" function of the Bio301 system, an automated EST sequence management and functional annotation system [ 66].
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CEO of Professional Science Editing for Scientists @ prosciediting.com