Sentence examples for microarray datasets did from inspiring English sources

Normalized microarray datasets did not result in significantly altered gene expression for zebrafish housekeeping gene β-actin2 (172 probes in our arrays).

Several factors impede a straight-forward analysis of microarray database content: standards for data submission vary between different databases, some microarray datasets do not provide raw data and on the experimental side, protocols and experimental conditions can differ between diverse laboratories conducting microarray hybridizations.

These observations raise the possibility that VEGF-A/FLJ10540/PI3K/AKT might be in the same pathway, despite the fact that the gene expression patterns of AKT in our lung cancer microarray dataset did not exhibit any correlation with FLJ10540.

The microarray and qRT-PCR derived fold-changes between elongation zone (IN2) and secondary growth dominant (IN9 or IN5) zones are illustrated in Additional File 3. The weakly regulated gene number one, identified as differentially expressed in the microarray dataset, did not show differential expression between IN2 and IN9 in the qRT-PCR analysis.

Since the underling samples in the random miRNA microarray dataset do not correspond to the samples in the random mRNA microarray dataset, high miRNA-mRNA correlations obtained from this random miRNA-mRNA dataset are a result of chance and therefore are considered as false.

Iterative comparisons of different microarray datasets were done with MAS 5.0 comparison analysis as previously described with modifications [ 48].

The individual studies correspond to eight independent microarray datasets that do not share samples or microarrays, and include brain gene-expression measurements from one-day-old and forager honey bees.

For both root and leaf development, the protein-protein interaction datasets did not have much influence at all compared to the microarray datasets on any of the pairs.

13 As this preprocessing step is highly dataset dependent (eg, SAGE datasets/spots are treated differently than microarray datasets), BioNetwork Bench does not currently offer a streamlined approach to automate the aforementioned pre-processing steps.

But when pooled with our DNA microarrays dataset they did not form a tight cluster.

Simulation results show that the proposed methods provide more accurate missing value estimation in six testing microarray datasets than the existing regression-based methods do.