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We were able to use the mean expression value of any gene from one-channel of NSCLC cell lines to estimate the log10(GeneXreference).
One potential solution is to use the mean expression values of all genes in a sample as the endogenous control, as proposed by Mestdagh et al. [ 15], and calculate ΔCT by subtracting this mean CT value from the CT value of all genes in the sample.
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By using the mean expression value of all expressed miRNAs, we identified the most stable candidate reference genes for subsequent validation.
A robust method using the mean expression value was used to identify the most stably expressed miRNAs: let-7a, miR-26a, miR-345, miR-425 and miR-454.
After data normalization using the mean expression value of all miRs detectable in the respective samples, 60 miRs showed a down-regulation and 33 miRs an upregulation of at least threefold after the treatment.
Relative expression data were then normalized using the mean expression value, calculated on the overall miRNA expression in each array, according to a Ct detection cut-off of 35 PCR cycles as described by Mestdagh et al [23].
Thus, super-clusters were generated using the mean expression profiles of the previously obtained clusters.
The first two measurements were calculated using the mean expression as a cut-off.
Missing values were imputed for the PCA using the mean expression of that gene for the experiment.
Fold changes for each biological replicate were calculated using the mean expression values from the immature brain samples.
Each gene was rescaled using the mean expression value of control samples to give a relative normalized value.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com