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A first approach that used metabolite mass spectrometry data of multiple expressed samples was introduced by Fiehn et al[224].
(F) Mammol/Lalian cell (293T cell) expressed EBOV NPΔ451 739 protein purified following the same protocol as described above for E. coli expressed samples.
False discovery rate was estimated based on the probability of encountering the observed number of differentially expressed samples in the treated group, given the total number of observed differentially expressed samples in both groups, under the empirically determined distribution derived from the null hypothesis that the differentially expressed samples are equally distributed in both groups.
As above, NTC did not amplify, and -RT controls were more than 6 Ct above the lowest expressed samples.
Given that DI is produced in bacteria however sufficient measures should be undertaken to ensure expressed samples are free from lipopolysaccharide.
Average RPKM from two biological replicates of each control (Ren) and TRIM33 shRNA expressed samples was then used to calculate fold change with log2 scale.
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As requested by the software, Ct values were converted to linear expression quantities by 2-ΔCt using the highest expressed sample as calibrator.
The geometric mean of the Ct value of the endogenous control genes was used to normalize the data and the lowest expressed sample was used as a calibrator.
Subsequently, technical replicates were averaged and relative quantities (fold changes, FC) were calculated based in the less expressed sample for each assay.
The expression level for determining high expressing samples was defined as one standard deviation above the mean value for all normal ovarian RE, for each specific target gene.
The 25% highest Wnt expressing samples were compared to the 25% lowest Wnt expressing samples for expression of CUX1, Glis1 and the EMT markers Cdh1, Cdh2, Ocln, Snai1, Snai2, Vim and Twist.
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