Sentence examples for microarray datasets there from inspiring English sources

Furthermore, other than microarray datasets, there exist experimental or computational results such as those from ChIP-chip (eten et al., 2007), deep sequencing (Sultan et al., 2008), quantitative proteomics (Sharma et al., 2009) and in silico network simulations (Stojmirović and Yu, 2007, 2009), that may benefit from enrichment analysis.

In our microarray dataset, there was a small but statistically significant upregulation of Kcnj11 (pore-forming Kir6.2 subunit of the β cell KATP channel) in oxidant-vulnerable CRI-G1-RS cells, which was associated with increased KATP current density in this cell type (unpublished preliminary data).

To be more specific, in a typical microarray dataset, there are thousands of gene features.

Furthermore, as has been previously shown for other microarray datasets [35], there was very little overlap between the five studies despite the similarities in study design.

In a high-dimensional microarray dataset, because there are thousands of genes, it is inefficient to adopt an evolutionary algorithm such an artificial bee colony directly in a microarray dataset.

For each dataset from both collections of toy datasets and real-life microarray datasets, we have shown that there exists a value of the DDP which optimizes several characteristics representing the goodness of the predictor set.

We first tested and validated our regulon mapping method in PCC6803 (see Materials and Methods) since there are multiple microarray datasets for this organism.

There are currently 41124 microarray datasets deposited in Array Express database in contrast to only 5745 RNA-sequencing experiments (accessed 01/03/2014).

There are several reports of microarray datasets produced using laser capture micro-dissected material and from clinical biopsies which have yielded only nanograms of RNA material [19], [22].

The method can be used to identify subtypes in any disease for which there are at least two independent microarray datasets of disease samples.

Although numerous investigations have compared gene expression microarray platforms, preprocessing methods and batch correction algorithms using constructed spike-in or dilution datasets, there remains a paucity of studies examining the properties of microarray data using diverse biological samples.