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Given that the CV and VMR were obtained using the mean transcript level per experiment, they act as estimates of transcript variation in response to perturbations in development, abiotic stress or natural genetic variation rather then simply a measure of experimental variation.
With TransCount we found estimates of transcript concentrations for each gene per sample.
Estimates of transcript amount were performed using the comparative threshold cycle method.
For many genes, estimates of transcript abundance are relatively unaffected by alignment strategy.
For NGen and bowtie2, we used read counts as our estimates of transcript abundances.
Estimates of transcript expression were obtained by counting reads aligning to exons of predicted gene models.
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For this, we used previously acquired data sets generated by nondestructive labeling methods, which provide more accurate estimates of transcripts' half-lives and disturb cell physiology less than methods involving blockage of transcription (Friedel et al. 2009).
The hypothesis that stochastic events cause greater variability of measurements from low amounts of starting material is supported by the observation that expression estimates of transcripts that show strong differences between replicates on average have only half the intensity of truly differentially expressed genes.
Assemblies provide rough estimates of transcripts.
The above-mentioned methods use different algorithms and assumptions so they produce different estimates of transcripts abundance.
The abundance estimates of transcripts separately for each time point (d 0, 9, 13, and 17 of the cold acclimation) and genotype ('Veyo' and 'Falster') were calculated using RSEM [ 64].
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