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We identified that the density of small RNAs mapping to intergenic regions was significantly lower compared to small RNA density mapping to paired/clustered genes (Additional file 1: Figure S6)(mean value 0.12 vs 0.54; p-value < 2.2e-16 2.2e-16
RNA density was measured with an Ultrospec 3100 Pro instrument (Amersham Biosciences, Piscataway, NJ, USA), and RNA quality was checked with the 2100 Bioanalyzer (Agilent Technologies).
Finally, and most tantalisingly, the high resolution images of 39S porcine LSU reveal an RNA density that is separate from 16S rRNA.
For intergenic regions that had high small RNA density, we found these small RNAs are often in discrete sections or adjacent to predicted genes.
In a second group, small RNA density was proportional to RNA-Seq density at the xUTR (top right quadrants in Fig. 4a-b, rliver = 0.53, rspleen = 0.42).
In the present work, mean trends were established from the mean value of three independent measurements of ρ (transcript density or total RNA density) at every position.
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Density for the Rev helices and RNA was very clear and Rev molecules from the Rev-dimer structure (Daugherty et al., 2010b) and an RNA fragment from IIB RNA NMR structure (Battiste et al., 1996) were fit into the protein and RNA densities, respectively, using rigid-body fit in Coot (Emsley et al., 2010).
RNA labeling density was evaluated using NanoDrop 1000 spectrophotometer (Thermo Scientific) and visualized using denaturing agarose gel-electrophoreses.
Indeed, the Spearman rank correlation between average RNA signal density and the corresponding CV was −0.58, indicating that transcripts with lower abundance have higher CV.
It was recently shown that RNA polII density is also enhanced at 3′-gene ends (Larschan et al. 2011) and the current model thus proposes that the Drosophila DCC acts to enhance transcription elongation, rather than initiation.
Comparing expression metrics from array intensities to RNA-Seq density shows a strong congruence.
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