Sentence examples for microarray dataset revealed from inspiring English sources

GSEA comparison of directly bound targets with the NKX2.2 knockdown/rescue microarray dataset revealed a statistically significant enrichment of NKX2.2 bound targets with NKX2.2 repressed genes (NES = −1.4; p<0.001; Figure 5F).

GO analysis of DEGs in our microarray dataset revealed that some of the most highly enriched categories among DEGs between germinal layers were common to both SG and LS, including regulation of transcription, cell adhesion, extracellular matrix, cytoskeleton, and neuron differentiation, as previously also found in the human embryo cortical germinal zones (Fietz et al, 2012).

Our meta-analysis of publicly available microarray datasets revealed that microarrays failed to detect multiple cytokine genes that have been linked to various human kidney conditions.

A direct comparison of 5178 ensembl genes with measured expression in both the DRS and microarray datasets revealed a reasonable correlation (Pearson correlation coefficient, R=0.68) between these two samples (see supplementary material Fig. S2 and methods in the supplementary material).

Indeed, analysis of a set of 19 genes that were downregulated in differentiated acini of human mammary epithelial cells in three-dimensional cultures against two independent breast cancer microarray datasets revealed that increased EphA2 levels are associated with poor patient prognosis [ 13, 15].

Meta-analysis of public microarray datasets reveals voltage-gated calcium gene signatures in clinical cancer patients.

Applying the module-based approach on a breast cancer microarray gene expression dataset revealed important biological processes and previously reported regulatory mechanisms underlying breast tumor progression.

The changes in transcription of these genes were compared with published microarray datasets and revealed a weak similarity of the microwave to light treatment experiments.

Previous analysis of the PubLiME dataset revealed that several genes display profound differences in their propensity of being detected as differentially regulated in a gene expression microarray experiment (Finocchiaro et al. 2007).

Here, we set up a bioinformatics platform by integrating three different microarray datasets to reveal key regulators involved in the metastasis of lung cancer.

By reannotation of the microarray for lncRNA, the expression information of the microarray dataset could be revealed for subsequent inspection [ 15].