Sentences with phrase «microarray gene expression profiling»

Miller, C.J., Kassem H.S., Pepper S.D., Hey Y., Ward T.H., Margison G.P. «Mycoplasma infection significantly alters microarray gene expression profiles.»

Not exact matches

One of these, his most influential, outlines his original use of microarray expression profiles as a phenotypic footprint for gene function.

Using quantitative RT - PCR we confirmed the expression profile of five genes (colony - stimulating factor 1 receptor [Csf1r], Cd68, Pex11a, Emr1, and Mcp1) in each of the 24 samples and found excellent agreement between the microarray and RT - PCR expression data (mean Pearson correlation coefficient = 0.91, microarray versus RT - PCR expression; Supplemental Table 3, http://www.jci.org/cgi/content/full/112/12/1796/DC1).

To detect novel changes in gene expression, we used a focused microarray platform to evaluate the expression profile of retinas from hypoxic animals compared to that in retinas isolated from control animals exposed to room air.

We offer a wide range of services, including capillary sequencing and genotyping, Illumina microarray - based gene expression profiling and genotyping, and next - generation sequencing (NGS).

This is an advantage of RNA - seq and microarray - based expression profiling, which can't always distinguish between multiple promoters of the same gene.

This will be achieved by exposing the coral to seawater with high calcium concentrations to induce an alteration in gene expression profiles, identified using a DNA microarray analysis.

Calcification rate measurements and gene expression analysis by microarray RNA transcriptional profiling at two time - points (midday and night - time) revealed several genes common within mammalian gene regulatory networks.

Unfortunately, direct comparisons of gene expression profiles obtained in independent, publicly available microarray experiments are typically compromised by substantial, experiment - specific biases.

The Gladstone team had profiled changes in gene expression using DNA microarrays, which provides an unbiased method for identifying key biological pathways.

Proteomic analysis to profile protein abundance resulted in the identification and relative quantification for 912 proteins with two or more unique peptides and 86 proteins with significant abundance changes after treatment with the neurotoxins, while microarray analyses to profile gene expression revealed 181 genes with significant changes in mRNA after treatment.

Another widely used technology to profile gene expression levels is microarrays.

The aim of his research was to use microarray gene expression data in order to characterize ageing in different human tissues and identify the age at which major changes in genetic expression profiles occur.

Quantitative real time PCR (qRT - PCR) is accepted as the gold standard for expression profiling, so we next compared both our RNAseq and the microarray expression estimates to a panel of qRT - PCR TaqMan gene expression assays (Figure 2C — F).

Comparison of gene expression profiles obtained by Q - PCR (left panels) and microarray analysis (right panels).

Specifically, we have generated clusters of transcripts that behave the same way under the entire spectrum of the sixty - seven experimental conditions; we have assembled genes in groups according to their time of expression during successive days of ES cell differentiation; we have included expression profiles of specific gene classes such as transcription regulatory factors and Expressed Sequence Tags; transcripts have been arranged in «Expression Waves» and juxtaposed to genes with opposite or complementary expression patterns; we have designed search engines to display the expression profile of any transcript during ES cell differentiation; gene expression data have been organized in animated graphs of KEGG signaling and metabolic pathways; and finally, we have incorporated advanced functional annotations for individual genes or gene clusters of interest and links to microarray and genomic expression during successive days of ES cell differentiation; we have included expression profiles of specific gene classes such as transcription regulatory factors and Expressed Sequence Tags; transcripts have been arranged in «Expression Waves» and juxtaposed to genes with opposite or complementary expression patterns; we have designed search engines to display the expression profile of any transcript during ES cell differentiation; gene expression data have been organized in animated graphs of KEGG signaling and metabolic pathways; and finally, we have incorporated advanced functional annotations for individual genes or gene clusters of interest and links to microarray and genomic expression profiles of specific gene classes such as transcription regulatory factors and Expressed Sequence Tags; transcripts have been arranged in «Expression Waves» and juxtaposed to genes with opposite or complementary expression patterns; we have designed search engines to display the expression profile of any transcript during ES cell differentiation; gene expression data have been organized in animated graphs of KEGG signaling and metabolic pathways; and finally, we have incorporated advanced functional annotations for individual genes or gene clusters of interest and links to microarray and genomic Expression Waves» and juxtaposed to genes with opposite or complementary expression patterns; we have designed search engines to display the expression profile of any transcript during ES cell differentiation; gene expression data have been organized in animated graphs of KEGG signaling and metabolic pathways; and finally, we have incorporated advanced functional annotations for individual genes or gene clusters of interest and links to microarray and genomic expression patterns; we have designed search engines to display the expression profile of any transcript during ES cell differentiation; gene expression data have been organized in animated graphs of KEGG signaling and metabolic pathways; and finally, we have incorporated advanced functional annotations for individual genes or gene clusters of interest and links to microarray and genomic expression profile of any transcript during ES cell differentiation; gene expression data have been organized in animated graphs of KEGG signaling and metabolic pathways; and finally, we have incorporated advanced functional annotations for individual genes or gene clusters of interest and links to microarray and genomic expression data have been organized in animated graphs of KEGG signaling and metabolic pathways; and finally, we have incorporated advanced functional annotations for individual genes or gene clusters of interest and links to microarray and genomic resources.

The results show comparable gene expression profiles between microarray and Q - PCR data.