Sentence examples for Microarray data generated from from inspiring English sources

Microarray data generated from this study provide insights into the mechanisms of endocrine disruption in this species, most notably the significant upregulation of the biological processes involved in cholesterol and lipid metabolism after subchronic androgen exposure.

However, microRNA microarray data generated from the same amount of total RNA were not normalized in general, because we know that the amount of microRNA varies depending upon cell types, such as normal tissue vs. cancer [15].

B, The CACGTGTC motif (containing the ABRE consensus) attained the highest MAMA score when microarray data generated from Arabidopsis roots subjected to NaCl stress were analyzed.

C, The CGACCGAC motif (which contains a DRE) attained the highest MAMA score when human microarray data generated from Arabidopsis roots subjected to NaCl stress were analyzed.

A, The TGGCGACA motif (containing a ZDRE) attained the highest MAMA score when microarray data generated from rice roots subjected to zinc deficiency were analyzed.

In microarray data generated from A. thaliana subjected to NaCl stress (Dinneny et al. 2008), the motif containing an abscisic acid (ABA -responsive element (ABA -responsive]C), which is a cis-element responsive for ABRE dehydrACGTG[G/T]Ctemperature, and high salinity (Narusaka et al. 2003), yielded the highest MAMA score (Figure 4B, Additional file 8 online).

The microarray data generated are available from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus [ 28] under accession code GSE57677.

We have compared microarray data generated on Affymetrix™ chips from standard (8 micrograms) or low (100 nanograms) amounts of total RNA.

Based on the Genevestigator from the microarray data generated by Schmidt et al [ 35] and Kilian et al. [ 36], AtHDA19 and AtHDA9 expressions significantly predominate other class I histone deacetylases in all the vegetative parts as well as developmental stages of the plant.

Cooperative modules were identified from prognosis data, which comprised microarray gene expression data generated from cancer patients and a prognosis that was classified as either good outcome (longer survival time) or bad outcome (shorter survival time).

One of the limitations of this analysis is that we compared the power of the two microarray platforms using data generated from a single 5-FU-sensitive and -resistant cell line model.