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The yield of qRT-PCR product was assessed by plotting the cycle threshold values versus the log10 numbers of input DNA copies.
Standard curves were generated by plotting the cycle threshold (CT) values of the qPCR reactions from serially diluted DNA.
The standard curves were constructed by plotting the cycle threshold vs. the concentration of DNA (log10 scale).
The efficiency of primer binding was determined by linear regression by plotting the cycle threshold value versus the log of the cDNA dilution [ 39].
The efficiency of the primer binding was determined by linear regression by plotting the cycle threshold value versus the log of the cDNA dilution (Soto et al. 2010).
Standard curves (tenfold dilution series) were generated for Senegalese sole TauT and eEF1a1 by plotting the cycle threshold (Ct) obtained in qPCR analysis versus the logarithm of standard copy numbers (CN) and performing a linear regression (Bustin 2000).
Similar(47)
Final standard curves were calculated for each pathogen by plotting the threshold cycle value against the bacterial number (log (colony forming units) per milliliter) via linear regression.
Standard curves were made by plotting the threshold cycle of known CCR5 and HIV-1 copies per reaction.
A standard curve was created by plotting the threshold cycle (Ct) versus the known copy number for each plasmid template in the dilutions.
Standard curves were constructed using the mtDNA hg H and non-hg H gDNA standards by plotting the threshold cycle values vs. the common logarithm of the initial number of template molecules.
For the estimation of mutant DNA frequencies standard curves were produced by plotting the threshold cycle values (Ct values) versus the logarithm of % frequency of mutant (V136) DNA in the standard plasmid DNA pools.
More suggestions(15)
by plotting the inhibition
by perpetuating the cycle
by plotting the conductance
by plotting the deviance
by breaking the cycle
by plotting the relationship
by plotting the deformation
by plotting the incidence
by plotting the number
by plotting the degree
by plotting the sample
by plotting the log
by plotting the generalization
by plotting the sensitivity
by plotting the amount
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