Sentence examples for microarray data generally from inspiring English sources

Control-gene-normalizing the microarray data generally improved correlation, but the moderate extent of this improvement indicates acceptable robustness of the control genes used.

This is mainly because microarray data generally has strong background-signals that make the comparisons of expression levels between genes within a single sample impossible [ 44, 45].

In support of this, the sequences that produced relative expression results that were not in agreement with the microarray data generally also had lower E-values, or were transcripts derived from large gene families.

Therefore, we regard the microarray data as generally reliable.

Two-color microarray data analysis generally consists of two stages.

In microarray data analysis, generally, the number of features in the final feature set is far smaller than the total variables.

Our results indicate that when identical transcripts are targeted by the two methods, correlations between qRT-PCR and microarray data are generally strong (r = 0.89).

The use of qRT-PCR for cross-validation of microarray data is generally limited to the most significant differentially expressed genes.

Our data indicate that correlations between qRT-PCR and microarray data are generally strong; a result that is particularly encouraging for those researchers with access to only very limited amounts of rare or unique test specimens.

Our qRT-PCR analysis of selected genes with different fold changes in the 0.5 h group also confirmed that the microarray data were generally reliable, although the exact fold changes might slightly vary between the two sets of data.

As for the L1 and iL3 data, this suggests that the dynamic range over which the observed experimental L2 microarray data fall is generally correct, though somewhat constrained compared with the actual differences in observed expression.