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The mapped reads from two biological replicates were subsequently analyzed by Cufflinks (version 2.1.1) to estimate the transcript abundance [ 75], and the expression level of each transcript was indicated as a FPKM value.
Briefly, the reads were aligned to a transcriptome index generated from Ensembl annotations (v79), using RSEM (RNA-seq by Expectation-Maximization) to estimate the transcript abundances28.
We are able to estimate the transcript abundance of and the differential expression (DE) between the two parent-specific alleles in the rice hybrids.
Using ΔCt analysis, normalized data were used to estimate the transcript copy number in infected mosquitoes.
The same procedure was used to estimate the transcript abundance of each gene lineage in Z. mays.
We introduced RNA-Skim, a lightweight method that can rapidly and efficiently estimate the transcript abundance levels in RNA-Seq data.
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Presumably, the higher the correlation is, the more accurate the method is in estimating the transcript abundance from RNA-Seq reads.
Based on these results, we believe that our PDEGEM can improve the accuracy in modeling and estimating the transcript abundance and isoform expression in RNA-Seq data.
A standard curve of the 73 nt amplicon MP gene was developed using known 1010 101 copies of in vitro synthesized RNA transcript to estimate the copy number of RNA transcript in the citrus leprosis samples.
With the Rcapture R package we estimated the transcripts population size to be 68,904 with a standard error of 210.
Furthermore, accurately estimating the transcript-level expression for all genes of all samples in a study may lead to improvements in molecular based diagnosis or prognosis tools, as well as in clustering of samples, e.g for cancer subtype discovery.
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