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In order to define genes that were differentially expressed in hibernating compared to summer active bears, we used P < 0.01 and log2FC > 0.5 where FC is fold change, the mean expression value in the hibernating bears divided by the mean expression value in the summer active bears, as the cutoff for differentially expressed genes (as described in Methods).
Log2 ratios between tumor and normal samples were calculated by subtracting the expression values (log2-transformed absolute reading) of each tumor sample by the mean expression value of all normal samples included in the dataset.
Due to the stochastic nature of evolutionary algorithms, 20 runs were performed for each inference task, and rMSE values, normalised by the mean expression values (rMse/Mean), were averaged across these.
To exclude a potential bias of the gene selection at baseline, we analyzed the correlation of the biological response determined by the mean expression value of the selected 15 IFN-induced genes with the baseline values of all genes on the array.
Missing values were replaced by the mean expression values of the according genes.
RpoS dependence of genes is represented by the mean expression ratio (MER) of WT and rpoS mutants.
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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.
Expression data were normalised by subtracting the mean expression of each gene and then dividing by the s.d.
Expression fold changes were obtained by dividing the mean expression level of a transcript in one strain by its mean expression level in another one for all the possible two by two strains combinations.
Gene expression values were rescaled as relative gene expression values, calculated by subtracting the mean expression value across samples from the gene estimate and dividing by the standard deviation across patients.
Li,k is obtained by calculating the mean expression value observed in MPk for the given sample, si.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com