Sentence examples for microarray analysis approach from inspiring English sources

Using an unbiased microarray analysis approach on hippocampal tissue, our study compared the effects of a brain permeant TZD treatment in younger and older animals, and showed that while age-dependent gene signatures were clearly present at both the gene (Fig. 6) and pathway (Table 2) levels, PIO effects on gene expression were virtually absent.

Finally, to identify additional markers capable of predicting apoptotic response to this agent, we used a cDNA microarray analysis approach.

We chose the microarray analysis approach to assess the co-expression of a large amount of genes, including those that are not looked at in common analyses.

We compared the leaf RNA sequencing dataset with the present leaf dataset to demonstrate and confirm that our microarray analysis approach towards transcriptome profiling was appropriate.

We compared our whole-genome microarray analysis approach to the main phylogenetic groups of the ECOR collection previously defined and based on MLST data.

Furthermore, the power of the microarray analysis approach lies in its ability to detect genome-wide, coordinated, or similarly regulated differential gene expression, pointing to perturbed signalling pathways and importantly downstream molecular processes.

Consequently, classic microarray analysis approaches might not produce optimal results, because they tend to discriminate gene expression profiles on the basis of the experimental settings in which they have been produced rather than on the basis of the stimuli they are responding to (for example a drug treatment).

Differential expression was determined using the significance of microarray analysis (SAM) approach and miRNAs with a false discovery rate (FDR) of 10% or better and modulated by >30% were selected for further validation studies.

Here, we have developed a microarray data analysis approach based on the similar concept as the simple, yet highly powerful and versatile sequence alignment comparisons (e.g. BLAST) for matching an unknown test DNA sequence against a comprehensive reference database of previously sequenced samples.

Interpretation of the glycan microarray analysis was approached from the perspective of cell wall polysaccharide classes and the results are presented as heatmaps.

Many microarray data analysis approaches are based on case-control study designs like comparing treated and untreated cells or matched disease and control tissues.