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The evolution and functional significance of the genome variation in GC content and codon usage bias have been widely reported between organisms and also within a genome; however, the underlying causes of these variations remain poorly elucidated and there has been a long debate over whether these variations are selected or neutral traits [ 58].
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The model variations were selected based on the interaction among the studied variables, namely, six moisture contents ranging from 0.03 to 0.22 m3 m−3, five wet bulk densities ranging from 1.3 to 2.0 Mg/m3 and six tillage depths ranging from 0.10 to 0.37 m.
The remaining seven (12.5%) variations were selected by dominant amino acids in the presence of a specific HLA type.
Cell lines harbouring a high level of the sequence variations were selected for further studies.
Thirty-two of the most common disease-causing ABCA4 variations were selected for the initial screen.
Of these network properties, only weighted size and genetic variations were selected as variables that explained the number of CGVs.
To verify the large deletions and inversions predicted by pindel, a subset of those predicted large structural variations were selected for PCR verification.
The reference gene for normalizing cDNA concentration variations was selected from four candidates, actin, elongation factor 1α (EF-1α), elongation factor Tu (EF-Tu), and serine/threonine-protein phosphatase 2A (PP2A).
Four missense and two deletion variations were selected for this study because they were expected to cause functional alterations on pol ι on the basis of the nature of the changes, positions in the pol ι catalytic core, and predicted effects.
That is, under the geometric condition, the top ten stations with most uniform weight variation are selected, and the station with the highest topographic weight is chosen for the next network station.
Sites comprising high levels of variation are selected first, because these represent the observed intraspecific variation very efficiently (Fig. S4).
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