Sentence examples for microarray data reflecting from inspiring English sources

Cluster analysis of the microarray data reflecting the expression of 120 PK families was calculated in the 54 different tissues (Fig. 4).

Microarray data reflecting the expression pattern of cell adhesion molecules and cytoskeletal elements (day 8 day 20) were obtained as described previously [19].

Three lines of evidence point to the microarray data reflecting gene expression changes in planta; first, BLR was up-regulated 3.6 fold in BLR-OX compared to Col-0 (Table 1).

These results indicate that the microarray data reflects the transcript ratios for the majority of genes.

Quantitative real-time polymerase chain reaction (qRT-PCR) and immunoblot analysis on discovery set samples was used to verify that the geo-ancestral genes identified in our analysis of the microarray data reflect true changes in gene expression.

It should be noted that the microarray data reflects expression patterns of RPCs in all cell cycle phases, not just S phase, so an exact match of the percentage of RPCs positive for a given gene in the microarray analysis would not necessarily be expected in the [3H]-thymidine/DISH experiments.

Because gene transcription is dynamic, the microarray data reflect expression differences at 02 00 h only.

In addition to global changes, the DNA microarray data reflect the initial adaptation to methanol and thus enable the investigation of more specific changes resulting in activation of methanol-dependent genes or in repression of glucose-dependent genes.

One of the greatest limitations of microarray data reflects the underlying biology: the expression of mRNAs doesn't always translate into proteins because silencing RNAs and other mechanisms can block the translation process.

In the context that minimizing undesirable technical variation allows for more accurate analysis of gene expression and increased power for significance testing, we propose that the simple method described here, consisting of a universally available set of three criteria, can ensure that microarray data reflects biological differences as opposed to experimental variability.

A large number of methods have been developed for the analysis of microarray gene expression data, reflecting the tremendous complexity of the problem of transforming information on the expression levels of 20,000 genes into meaningful biological insights.