In order to reduce the computational complexity of the BER expression, we applied an interesting lemma based on the moment generating function of the interference power.
Applying the same analysis in T2DM patients versus controls, we also detected significant metabolic differences, albeit at lower levels of statistical significance, due to the low number of controls.> To obtain more insight into the pathology behind the differences in gene expression, we applied pathway analysis using Gene Set Enrichment Analysis (GSEA, [ 23]).
To demonstrate the function and efficacy of this fNC for self-activating and imaging the dynamics of mRNA expression, we applied it, as a proof of concept, to image the dynamics of mRNA sequential expression during neural stem cell (NSC) differentiation.
To identify the associations between the characterized cytogenetic features of B-ALL and low levels of HDAC7 expression we applied the Wilcox test.
To improve surface expression, we applied the pharmacological chaperone approach by treating cells with atropine or other antagonists.
For quantification of gene expression we applied the comparative Ct method, which was normalised by applying a geometric mean of 3 endogenous housekeeping genes (18 s rRNA, β actin and cyclophillin) [ 57].
To test whether exogenous application of auxin had a similar effect on AIP1-2 expression, we applied the synthetic auxins 2,4-Dichlorophenoxyacetic acid (2,4-D) or 1-Naphthaleneacetic acid (1-NAA) to the growth medium of AIP1-2-mCherry-expressing seedlings.
To positively control for transgene expression, we applied HA-tagged βI-/ βIII-/ βV-tubulin expression plasmids.
As a measure of co-expression, we apply the widely used Pearson correlation coefficient.
For statistical analysis of the expression data we applied the FunDaMiner system [ 145].
