The NMR signal is influenced by many experimental and sample dependent parameters, including analytical variants as sample preparation, FIA parameters, and NMR experimental parameters.
The NMR signal intensity is essentially related to the concentration (actually, to the number of nuclei responsible for the signal), although influenced by many experimental and sample dependent parameters.
The paper provides several simulated examples, a small empirical example to demonstrate proof of concept, and a larger empirical example based on many experimental conditions and large samples that demonstrates that the individual models capture virtually all the variance in aggregate first choices traditionally modeled in discrete choice experiments.
In our earlier studies, we have also pointed out that in many experimental designs, particularly when samples originate from different genetic backgrounds (e.g. different individuals), the presence of sequence variants within probe target sequences may be a very significant source of errors [ 8, 12].
Gene expression levels may be influenced by subjects' genetic background, age, gender, and environmental exposures as well as by many experimental variables relating to clinical sampling, processing, and data analysis.
Our design does not allow for a true ANOVA analysis (e.g. there is only one true plot) and this analysis is used here as if our subplot measurements were independent samples (noting that many experimental designs use this approach without the caveats) and should be interpreted as such.
The non-parametric bootstrapping process generates different datasets many times by re-sampling the experimental samples with replacement.
The results obtained predict many features observed in the micrographs of experimental samples.
Although MALDI MS is capable of profiling small samples for qualitative information, adding labeling reagents, performing reactions, and mixing control and experimental samples often has limited the application of stable isotope labeling to many-fold larger samples.
