Sentence examples for many reference genes from inspiring English sources

How many reference genes should be used is dependent on the purpose of research.

What and how many reference genes used for calculation of normalization factors (NF) in parallel samples is thus a crucial determinant of the accuracy of expression quantification.

This broad U-shape curve suggests that inclusion of either too few or too many reference genes may detriment the robustness of data normalization.

Taken together, what and how many reference genes are sufficient for RT-qPCR data normalization varies on a case-by-case basis.

Unexpectedly the NF variation across samples does not exhibit a continuous decrease with pairwise inclusion of more reference genes, suggesting that either too few or too many reference genes may detriment the robustness of data normalization.

Many reference genes, assumed to have a stable expression have been used to normalize expression in transcriptomics.

When prior knowledge of the species composition and gene contents of the sequenced metagenome is unavailable, we can use as many reference gene sequences as possible (e.g. the entire set of genes from all available microbial genomes) to guide the inference of gene paths.

Also, now that an increasing number of detection methods are available, it proves impractical to use many different reference genes per crop.

First, we demonstrate that many commonly used reference genes fluctuate in a condition-specific manner beyond the limits of suitability when normalizing for target gene expression using qRT-PCR.

Although limitations are universally recognized, still many laboratories use reference genes without appropriate validation [ 6, 7].

Considering the species, there are many differences in reference genes stability evaluated in these studies.