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Among the candidate polymorphisms in the EGFR gene, we initially captured 39 SNPs in the promoter region, all exons including intron-exon boundaries (10 bp of the introns on either side) and the 3'-UTR of the gene because variants in these regions are most likely to affect gene function (Table 1).
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Although screening the entire PTGS2 gene would be theoretically preferable because variants in the coding and non-coding regions could tag other functional SNPs, previous reports involving these variants suggest no significant effect on COX-2 activity [ 48] or on cancer risk [ 16, 21, 25, 28- 30, 32, 33, 35- 43, 45, 46].
This leads to the hypothesis that some people with reduced ability to respond might be more susceptible because of variants in these generic stress response genes".
Coding regions are targeted because the functional consequences of variants in these regions are much better understood than those in noncoding parts of the genome.
Because of this close physical linkage, allelic variants in these genes very likely cosegregated.
The conserved protein regions were assumed have more constraints related to protein function, and the virus would have fewer viable options to generate escape variants in these regions [ 12], because the escapes made in these conserved regions would carry a higher fitness cost [ 38, 39].
These findings warrant follow up in large patient samples, because more variants in immunosuppressive pathway genes are potentially associated with prognosis of breast cancer.
Druse proteins involved with inflammation and innate immunity (e.g., amyloid-β, immunoglobulin light chains, factor X, C3, C5b-9 complex) have received particular attention because sequence variants in several complement proteins are associated with increased ARM risk [13], [14], [15], [16].
We hypothesize that as a consequence of high levels of sequence polymorphism in Pacific oysters, Q-PCR amplification is sub-optimal in some individuals because sequence variants in priming sites results in poor primer binding and amplification in some individuals.
For example, the variants with the top two strongest effects ("1" and "2") in Figure 3B are not identified because others variants in linkage are selected by MLMM and included as covariates.
The inconsistency among samples in six of the duplicates was mostly due to removal of real alleles, because the variants in question had low frequency on per individual basis and were highly similar to more common variants.
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