Sentence examples for between subsets of interest from inspiring English sources

Determining fold-changes in gene expression levels between subsets of interest is often a major aim of microarray studies.

Determining fold-changes in gene expression levels between subsets of interest is often a critical aim of microarray studies.

These data indicate that our oligo-array platform is able to accurately predict the direction of change of gene expression level (i.e. either up or down regulation) between subsets of interest.

These data indicate that the direction of change of gene expression levels (i.e. either up or down regulation) between subsets of interest is accurately predicted by comparison of average microarray expression scores.

We observed a similar trend towards poorer correlation for genes that exhibited fold-change differences of <1.5 between subsets of interest based on microarray expression scores compared to those with fold-change differences of >1.5.

Interestingly, we noticed a trend towards poorer correlation for genes that exhibited fold-change differences of <1.5 between subsets of interest based on microarray expression scores compared to those with fold-change differences of >1.5 (data not shown).

To address this issue, we analyzed fold-change in average gene expression levels between our subsets of interest (e. g. tumor vs normal) by both qRT-PCR and RMA or MAS 5.0 microarray scores for the same genes.

The 48 genes were targeted for validation either on the basis of their differential expression between our subsets of interest (e.g. brain tumour vs normal brain specimens, leukemia specimens vs normal CD34+ stem cells) as determined by microarray analysis, or because they mapped to chromosomal regions of interest.

Before starting the proof, however, we must clarify exactly what the "subsets of interest" are.

Tree construction is initiated by obtaining the family of sample subsets of interest { A i } from the set of SNPs.

The mapping of modal clusters to cell subsets of interest is done by examining the statistical properties of each cluster.