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In general, the size of an effect on SI sufficient for an effect on phenotype is likely to vary substantially from transcript to transcript.
Since the time to splice is a distributed quantity, and splicing times vary from transcript to transcript, the variation in previously reported splicing rates may be strongly influenced by the temporal dynamic range of the method.
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Next, a pairwise transcript-to-transcript Pearson correlation matrix was calculated based on each transcript's profile across all samples.
From a pairwise transcript-to-transcript correlation matrix a weighted, undirected network graph was constructed using a Pearson correlation threshold cut-off of r ≥ 0.80.
The statistical approach employed centers on the principle of coexpression, based on the transcript-to-transcript comparison of the expression signal across the samples analyzed, by calculation of a Pearson correlation matrix.
Comparing the average standard deviation in mean expression per DGRP line for TE-associated transcripts to transcripts with no TEs in or within 10 kb indicates that TE-associated transcripts have a larger mean standard deviation, 0.33 vs. 0.28, (t-test; P = 1.0 e-22).
Mapped reads were normalized to transcript lengths to estimate transcript abundances.
Similarly, transcript VIII is identical to transcript VI but retains intron 3. Intriguingly, these alternatively spliced transcripts are differentially expressed in root and shoot tissues.
The P2 transcript and total bteA (P1 + P2) transcripts were determined individually and the ratio of P2 transcript to total bteA transcript was calculated.
However, their simultaneous presence was sufficient to transfer differential translational control from the native transcript to the reporter transcript.
Therefore, another possibility is that one of the transcripts that Ladd et al. cloned and identified as an alternative transcript to ASFMR1 is the FMR4 transcript.
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