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To quantify the cohesive effect of HR between two populations, we start by assuming that the two populations will converge due to HR at the rate 2ρπg10 − 20πg, where ρ is the recombination rate and πg is the average nucleotide divergence between the populations (i.e., the average nucleotide divergence between any two sequences which are chosen at random from each of the two populations).
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Since simulations were independent between the two populations, we used all the pairs of their combinations (100×100) for the analyses (Fig. S1A).
To further investigate the molecular difference between the two populations, we mechanically separated adherent neurospheres from migratory cells and performed microarray analysis of gene expression (Figure 4).
To test for differences in these relative estimates between these two populations, we performed nested analyses of variance for each caste separately with colony (within population) and population as factors explaining weight variation.
In order to assess the degree of overlap between the two populations, we determined their total volume and estimated the portion of this volume that was simultaneously occupied by the two groups.
Given the high statistical significance of the overlap between the two populations, we sought to use the high-resolution MDP data for fine mapping causal genes in loci that are significant according to the BXD panel.
To investigate the behavior of a sample protein with a size intermediate between the two populations, we have studied the in vitro aggregation process of YHKB, a fairly large protein having 486 residues and a molecular weight of 55 kDa.
When comparing the ranking and proportion of the five most common SPCs after particular first primary cancers between the two populations, we found that there was a similar order of the five leading SPCs after most selected first primaries, especially for kidney cancer, NHL, and leukemia (Table 2).
Because the sample size of persons 18 29 years was inadequate to detect a significant difference between the two populations we combined the 18 29 year-old and 30 49 year-old age categories, which displayed similar frequencies of clindamycin and erythromycin resistance, allowing us to compare resistance levels for similar age groups.
To compare patterns of W→S DAF skew between the three populations, we calculated pairwise correlations of U-norm in 40 kb and 1 Mb windows across the genome.
Just as with different results in different species, when results differ between two populations of the same species, we cannot distinguish real population differences from some sort of error.
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