Sentence examples for the shape of expression from inspiring English sources

The shape of expression profiles were characterized further.

The shape of the expression curve, as well as amplitude and timing of peak expression, varied between 1-hour and 4-hour sampling.

Note that the shape of the expression profile, not its absolute level, dictates its classification.

We conclude from the agreement with direct measurements of Fis protein and fis mRNA that reporter genes are a reliable tool for tracking the shape of the expression profile of the host gene.

To identify putative target-target interactions, the Pearson Correlation Coefficient (PCC), which is known to provide information about the "shape" of gene expression changes [ 47, 48], was used; an absolute PCC value of 0.3 was used as a cutoff.

In this second approach normalized profiles (NP) were used as input to the clustering algorithm to emphasize the "shape" of the expression profiles with time and to capture subtle differences in the up- or down-regulation of each gene, since these are not observed when absolute values or fold-change expression profiles are assessed.

We found that T4 concentration affected the timing of gene expression and the shape of temporal gene expression profiles.

Rules can always be expressed as branches in a tree, with the events as nodes in the shape of a regular expression.

These results show that T4 concentration affected the shape of temporal gene expression profiles but essentially all epidermal DEGs that were identified in both T4 treatments were regulated in the same direction by 5 and 50 nM T4.

Some genes in FC13 also fall into clusters NP2 and NP24 (Additional file 1), in which the shapes of the expression profiles in the two cultivations are similar, but the expression level is higher during D-xylonate production compared to the control (i.e. less down-regulated in NP2 and more up-regulated in NP24).

These strategies were deployed using various combinations of methods for calculating parameters that describe the shape of FDCs (polynomial expressions and probability distribution functions) and then methods for estimating these parameters at ungauged sites using available catchment characteristics (stepwise linear regression and random forests).