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The most accurate transcript pairs are returned as top-scoring classifiers.
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If sequence, as well as sequence context, introduces subtle adjustments to the final measured value of a transcript, then it may not be possible to know which measurement is the most accurate measurement of transcript abundance.
However, as amplicon sequencing could well result in a biased amplification of the higher abundant templates, we finally set up a splice variant specific quantitative real-time PCR (qRT-PCR) using a set of variant specific reverse primers (Supporting Information Table 2 and Supporting Information Fig. 3), which is certainly the most accurate method to quantify transcript abundances.
Reverse transcription quantitative polymerase chain reaction (RT-qPCR) has been recognized as the most accurate method for quantifying mRNA transcripts, but normalization of samples is a prerequisite for correct data interpretation.
When all ASPic predicted introns on the complete C. elegans genome are given as evidence to GeneID, our combined ASPic-GeneID system is found to be the most accurate in predicting exact nematode transcripts.
Reverse transcription quantitative polymerase chain reaction (RT-qPCR) has been recognized as the most accurate, sensitive, and easy method for quantifying mRNA transcripts in biological samples [ 1, 2].
The actual number of clusters was fine-tuned by examining the groups of transcript abundance profiles with smaller and larger clusters for the best and most accurate representation of the cluster profile in each cluster.
The most accurate gene finders found by nGASP were 'combiner' algorithms, such as Jigsaw, which made use of transcript and protein alignments and multi-genome alignments, as well as gene predictions from other gene finders.
Reverse transcription (RT) quantitative real-time PCR (qPCR) is the most accurate and easy-to-perform technique to measure the expression level of a selected gene of interest by quantifying mRNA transcripts.
"This is a more accurate transcript".
Who was most accurate?
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