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This observation was consistent with the fact that 60% of transcription was devoted to ribosomal ribonucleic acid (RNA), 32 because genes with higher expression levels tend to be clustered.
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It should be noted that the negative correlation between GL and TS may be related to the analytical formulation used to compute TS (see Materials and Methods) because genes with high expression levels in one or a few tissues (i.e., high PE) will often, but not always, have high TS as well.
Positive matches with SOX genes (SOX2, SOX4, SOX21) were discarded after manual inspection, because the same contigs also matched other SOX genes with higher scores.
Because genes with lower Ka/Ks values had higher residual genetic robustness, we can infer that there is weak canalizing selection on expression robustness to genetic perturbations, but that this is often overwhelmed by selection for environmental plasticity.
Because genes with low expression generally had higher levels of TF-responsiveness than highly-expressed genes, we used floating thresholds to separate these groups of genes (see details in Methods).
Gene expression profiles were also used as an evidence for inferring protein subcellular localization because genes with similar expression patterns or relatively high correlation coefficient are potentially within the same cellular compartments or pertaining to relational functionality [57].
This is probably mainly because Human has more genes with high tag-position and less with low tag-position, as shown in the gene density curve of Fig 2A which is shifted to the right.
This selection must give greater chances not only to chromosomes with lower cost, but also to chromosomes with greater cost because they may have some genes with high quality.
Because there is a possibility that genes with high expression show weak response to perturbations simply due to saturation or miscalibration of microarray signals, we tested the sensitivity of the microarray by serial dilution of mRNA [ 14].
Because and are highly negatively correlated (r = -0.99), genes with high positive have negative and vice versa.
The distributions of all data were significantly different from normal because of a large number of genes with low hybridisation signals and few genes with high signals.
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