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The three main methods for validating individual cases [ 33] are probabilistic approaches, expert opinion and algorithmic-based approaches.
It is worth noting that Sanger sequencing, typically the "gold standard" for validating individual SNPs [ 23], is not likely to be useful for validating haplotypes.
Rectifying these potential artifacts manually is challenging due in part to the very large size of data present in FCPD and also due to the difficulties of validating individual data.
Galan et al. [ 13] developed a probabilistic model for determining the read coverage threshold T1 (minimum number of sequences per individual required for reliable genotyping) for validating individual genotypes at a given confidence level.
Therefore, in addition to validating individual predicted direct miRNA-122 target gene expression to assess functional efficiency of miRNA-122 inhibition in trout, we focused on analyzing the expression of non-target markers of key hepatic metabolic pathways to elucidate the underlying (indirect) molecular mechanisms for the observed metabolic consequences in vivo.
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We did not attempt to validate individual SNP dominance effects because the validation population was not large enough to have sufficient power for this.
These comparisons do not validate individual cases or provide a measurable estimate of validity.
The method was tested by carrying out an experimental role play to validate individual agent tasks, focusing on the ability of agents to generate beliefs and preferences about their environment.
It is making it possible to validate individual targets and synergistic molecular relationships that constitute either oncogene or non-oncogene dependencies of the tumor, or that increase sensitivity to existing FDA-approved drugs or compounds in the late stages of development.
Therefore, the predictive value we found is not a validation for all individual rules in the system and we did not attempt to validate individual rules.
Our objective here was to validate individual observations of this seasonal discrepancy in peak mortality between historical epidemics and modern empirical data.
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