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The Spearman's correlation coefficient (r) was calculated to determine the relationship between measures of sequence diversity and the estimated year of infection.
We showed that for the majority of protein families there exists a statistically significant linear correlation between measures of sequence similarity and average loop structural similarity.
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The correlation analysis between the measures of sequence and structural similarity, linear/nonlinear regression analyses and cluster analysis were performed using Splus version 6. Pearson and Spearman correlation coefficients were calculated to quantify the accuracy of linear correlation.
Our results indicate that even longer protein loops can not be viewed as "random coils" and for the majority of protein families in our test set there exists a linear correlation between the measures of sequence similarity and loop structural similarity.
This problem is particularly acute with previous studies of mammalian transposons and non-LTR retrotransposons that have relied upon measures of sequence divergence between extant elements and their ancestral consensus sequences as estimates of element age.
There was no significant difference between patients with MSA and controls in the measures of sequence detection (manual sequence retrieval, ANOVA MSA-control, effect of group, F 1,18)=0.7, p=0.42).
In the previous section we have described the relationships between measures of gene expression and the length and the GC content of intergenic sequences.
Furthermore, we demonstrate a relationship between connectivity and a measure of sequence conservation.
As with previous work [21], we used the simplest measure of sequence divergence, i.e., the percent of amino acid changes between the two sequences.
Sequence entropy is a measure of sequence conservation.
All sequences are compared to each other to generate a matrix of distance measures between each pair of sequences.
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