Sentence examples for microarray data seem from inspiring English sources

The mature software and normalization techniques make analyzing RNA microarray data seem like a breeze.

Common approaches for processing microarray data seem adequate for our approach.

The pictures based on microarray expression data seem to be different, as extremes of structural characteristics better scale as logrithmic functions of expression levels.

To this end, cytology together with expression microarray data deconvolution seem more likely to succeed [ 54, 55].

Although most of our best scoring promoters do not correspond with the genes identified in our microarray analyses (see below), these data seem to be meaningful because the predicted candidates belong to the same functional categories of those up-regulated in citrus epicotyls in response to PthA/PthC expression or in Xc-infiltrated leaves in the presence of Ch (Additional files 1, 2, 3).

Sequence identity between P. falciparum p43 and its human homolog is ~24% and based on microarray data p43 seems to be expressed at asexual life cycle stages of P. falciparum.

This is because of the following reasons: a) Some of the published microarray data do not seem to be covered by the existing repositories/databases.

9 Although these results were indicative of novel features of the involution process, statistical analysis of microarray data did not seem to include a multiple testing correction of the raw P-values.

In recent years, we have witnessed a deluge of new results coming from genome-wide microarray experiments, and the torrent of data seems likely to increase in the future.

The fact that up to 30% of all transcripts display expression profiles correlated to the beta actin ratio implies that RNA quality can act as a major source for the previously reported correlation structure in microarray data [ 28]. refRMA normalized data seems to be more sensitive to the RNA quality effect compared to MAS 5.0 data.

While these methods give an idea of transcript abundance or enrichment in a specific tissue, it has been demonstrated that the SAGE method is reproducible [ 46], provides an unbiased, quantitative report of gene expression, that may be correlated with microarray data [ 47, 48], and seems more efficient than EST-based methods for discovering novel genes and spliced variant transcripts [ 13].