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Validation of this method is shown as it applies to a finite element model that discretizes the structure in multiple RRVEs, whose properties are generated independently of the neighboring ones, and then are solved simultaneously.
Independent RT-PCR validation of this splice is shown in the right panel, with IR calculated using ImageJ analysis of autoradiograms.
The general work flow for identification, prioritization, hypothesis generation, and validation of pVDCs is shown in Figure 1.
The successful validation of the module is shown and further implications are discussed.
The validation of these sensitivities is shown in Figure 23.
Validation of the model is shown in Figure 3. Observed results from the cluster-randomised bovine intervention trial for Yongfu village are similar to the predicted results by the model.
Validation of identified peaks is shown in Figure 2 figure supplement 1B,C.
Validation of representative genes by qPCR is shown in Fig. 1A.
DYD = Daughter yield deviation, YD = Yield deviation, r = average Pearson correlation coefficient of the cross-validation runs, variance of cross-validation runs is shown in brackets.
A summary of training and validation series demographics is shown in Table 1.
The true phenotype of each validation sample is shown in color (blue for normal and red for IPF).
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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