Sentence examples for samples gene expression from inspiring English sources

Plotting the average DNA methylation and gene expression differences between PPR and PGR revealed 22 probes annotated to 12 genes that were more highly expressed and less methylated in PPR samples compared to PGR samples (gene expression cut-off greater than 2 and a DNA methylation cut-off of less than −0.2, Figure  3, Table  3).

Approximately 350,000 SNP-containing probesets were filtered out before summarizing gene expression intensities in the CEU and YRI samples (Gene Expression Omnibus Accession: GSE9703 [9], http://www.ncbi.nlm.nih.gov/projects/geo/).nih.gov/projects/geo/

Indeed, for a significant proportion of samples, gene expression based classification and IHC based classification differ, and it is currently unclear whether these cases behave clinically more like true ER positive or true ER negative cases[5].

To explore whether we can identify a gene expression signature of TAA disease from peripheral blood samples, gene expression profiles of 61 whole-blood RNA samples (training set) collected from 36 TAA patients and 25 controls were analyzed using the Applied Biosystems Human Genome Survey Microarrays representing 29,098 individual human genes.

In addition, because of the limited number of samples, gene expression datasets do not represent the real distribution of data.

To analyze these transcription patterns in different samples, gene expression was also assessed in mosquitoes originating from West Africa.

Therefore, based on partial correlation, we propose a directed approach specifically targeted at small-sample gene expression data.

For each sample, gene expression PCR was carried out using 2 µl of cDNA template with sequence specific primers.

The shrinkage estimate for partial correlation in [7] was formulated specifically for the inference from small sample gene expression data.

For each sample, gene expression was quantified using a standard curve and normalized against the expression of the endogenous control genes GAPDH and ACTB.

The technique can be applied in almost any multi-sample gene expression experiment, and holds equal promise for protein abundance experiments.