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Finally, in a recent work Beisel and Storz [ 11] demonstrated with microarray analysis and reporter fusions that Spot 42 plays a broader role in metabolism by regulating at least fourteen operons dominated by genes involved in uptake and catabolism of non-favored carbon sources.
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Signal compression of fold-change ratios is a common phenomenon that has been demonstrated with both oligo- and cDNA microarrays [ 17, 53] and has been attributed to the presence of cross-hybridization signals [ 54].
Previous studies have demonstrated that microarray data are validated with quantitative PCR data [38], [43].
Previous studies have demonstrated that microarray data are validated with quantative PCR data [47], [49].
In general, most microarray studies with single-gene validation demonstrate a correlation with microarray techniques (Rickman et al, 2008).
The method can be extended to other 3' expression microarray platforms as we demonstrate with human data.
In addition, we have demonstrated that microarray findings from one study can be confirmed in an independent study, using an entirely independent patient cohort and with microarray experiments being performed by a different research team.
In summary, we have demonstrated that microarray findings from one study can be confirmed in an independent study, using an entirely independent patient cohort and with microarray experiments being performed by a different research team.
For example, with the use of Affymetrix U133A and B microarrays, it has been demonstrated that the microarray data can be reannotated for lncRNA expression analysis [ 10].
The detecting ratio for methylation of APC gene of colorectal tumor samples increased from 46.7% with MS-PCR to 63.3% with the microarray, which successfully demonstrated that DNA microarray-based method not only can obtained the methylation patterns for the related genes, but also decrease the false-negative results of methylation status by the conventional MS-PCR for the investigated genes.
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