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Given the remarkable heterogeneity of glycans from biological samples, the variable differences create the challenge to locate the pairs of relevant glycans from two respective samples.
It should be noted that in studies using small numbers of patient samples, although genes might be identified that are truly differentially expressed between the samples, the variable expression patterns might be unrelated to the disease state.
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The early/transient-response genes were repressed relative to untreated samples, the variable-response genes were initially induced and then repressed and the continuous/late-response genes were both repressed (set 5) and induced (set 6).
While the linear regression model may perform better in terms of type-1 error rates in small samples, the variable-dispersion beta regression model and fractional logit regression model seem slightly more powerful at detecting a true non-zero difference between groups in a two-sample design.
We also show that education—in our sample, the variable is literacy has an important protective effect on cognition.
For each DNA sample, the variable region 1 2 (V1–V2) of the bacterial 16S rRNA gene was PCR-amplified using individually barcoded primer sets.
Even more important than genome relatedness per se was the degree to which related samples sampled the variable genome of the taxon of interest [ 19].
The maximum value of the two samples was the variable used.
The main drawback of typing on clinical samples is the variable quality and amount of DNA.
Section 3 describes the sample, the variables and the methodologies used in the study.
Next, the empirical distribution is used to sample the variables ((Z_t, Y_t)) from the joint probability distribution by using (8) and (10) in Section 2.3.
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