Sentences with phrase «gene expression levels»

This can then be used to create computational estimates of gene expression levels from any whole genome sequence or chip dataset.

Identifying adaptive and plastic gene expression levels using a unified model for expression variance between and within species.

The evolution of gene expression levels in mammalian organs Brawand, D. M. Soumillon, A. Necsulea, P. Julien et al. 2011.

Differences in gene expression levels between people of European versus African ancestry can affect how each group responds to certain drugs or fights off specific infections, report researchers from the University of Chicago Medical Center and the Expression Research Laboratory at Affymetrix Inc. of Santa Clara, CA.

Manor O and Segal E. GenoExp: a web tool for predicting gene expression levels from single nucleotide polymorphisms.

We can now explain observed relationships between genotype and disease by looking at the effects of the genotypes that lead to higher risk of the disease on gene expression levels in disease - specific tissues, including brain.»

The minor allele of rs25532 significantly decreased luciferase reporter gene expression levels by 15 — 80 %, depending on 5 - HTTLPR allele background and cell type.

It can efficiently introduce DNA into a cell to be incorporated into its genetic make - up, i.e. induce high gene expression level, especially in both human and mouse breast cancer cell lines, and mouse breast cancer model.

The method, PrediXcan, estimates gene expression levels across the whole genome — a better measure of biological action than single mutations — and integrates it with genome - wide association study (GWAS) data.

«For the first time, our study identified detailed gene expression levels in these granules.

Identifying adaptive and plastic gene expression levels using a unified model for expression variance between and within species Rohlfs, R. and R. Nielsen.

In addition, she is working to expand it beyond gene expression levels, to predict the links between diseases or traits and protein levels, epigenetics and other measurements that can be estimated based on genomic data.

Transcriptome studies such as the National Institute of Health's Genotype - Tissue Expression (GTEx) program aim to overcome this limitation by studying gene expression levels and regulation mechanisms and their relationship with diseases, instead of only DNA sequence.

An interesting question for the future will be the quest for the potential genetic variants that may regulate imprinting levels — iQTLs, analogously to eQTLs that affect gene expression levels.

To identify which gene products were being disrupted, Schmidt - Ott's team profiled and compared gene expression levels between the front and rear halves of Chironomus embryos.

But transcriptome studies also have significant limitations, such an inability to determine reverse causality — whether gene expression levels are altered by disease, or whether disease arises due to altered gene expression.

Under those optogenetic controls, gene expression levels reliably increased in vitro by a factor of 10 to 20.

Elevated gene expression levels distinguish human from non-human primate brains.

The team identified 85 small molecules that increased noise without changing average GFP gene expression levels.

Recently, groups have leveraged high - throughput gene expression and genotyping technologies to perform genome - wide assocation studies of gene expression, in which gene expression levels are considered a quantitative trait and significant correlations to SNP variation are identified.

Moreover, using a Bayesian deconvolution method to estimate methylation levels from the data [53], we found promoter methylation levels to be significantly inversely correlated (p value = 2.3e - 25) with previously published gene expression levels of T cells from human samples (Figure S1).

While previous studies have focused primarily on gene expression levels and alternative splicing patterns, an important aspect of the transcriptome, RNA editing, has been largely neglected.

«PrediXcan tells us which genes are more likely to affect a disease or trait by learning the relationship between genotype, gene expression levels from large - scale transcriptome studies, and disease associations from GWAS studies,» said study leader Hae Kyung Im, PhD, research associate (assistant professor) of genetic medicine at the University of Chicago.

Extensive effort has been devoted to improving the accuracy and sensitivity of statistical algorithms used to estimate gene expression levels and to detect differential expression in GeneChip - based expression analyses.

The evolution of gene expression levels in mammalian organs.

Roughly once - a-week blood draws followed, checking nutrient and gene expression levels in his body.

The researchers found that the gene expression levels in immune cells changed in response to the macaque's new social rank within 3 months of establishing the new groups, and the cells got better at fighting infection.

Engelhardt's group was responsible for mapping associations between genetic variants and gene expression levels on different chromosomes, a connection known as «trans - expression quantitative trait loci (trans - eQTLS).»

Such modifications, including methylation, acetylation, ubiquitination, and phosphorylation, often result in the alteration of gene expression levels that determine cell fate.

Furthermore, GNC and GNL act, at the gene expression level, in an additive manner with the GOLDEN2 - LIKE1 (GLK1) and GLK2 transcription factor genes, which are also important for proper chlorophyll accumulation.

Kim will quantify the gene expression levels from Glover's newest lines that are resistant to preharvest sprouting and compare those results with the list of differentially expressed proteins from the Korean cultivars.

His work stems from the understanding that cell function depends on a strictly organized network orchestrating intracellular and environmental factors that include bioenergetics and metabolic processes, regulatory mechanisms of gene expression levels, and the effects of specific factors and signaling pathways that combined provide a molecular framework to achieve normal cell function.

We show, for the first time, the influence of the gene expression levels demonstrating the power of «big data» to change how medical research is performed.

«In a way, we're modeling one mechanism through which genes affect disease or traits, which is the regulation of gene expression level.»

Many human traits — from gene expression levels to disease risk — vary between individuals.

Genomes that have been sequenced as part of a GWAS can be run through PrediXcan to generate a gene expression level profile, which is then analyzed to determine the association between gene expression levels and the disease states or the trait of interest being studied.

«Methods currently used for measuring gene expression generally rely on something called «relative normalisation», which means that gene expression levels in a sample can only be estimated relative to other genes in the same sample.

Dr Gilchrist said: «This study suggests that we may improve significantly on the widely used analysis methods for determining gene expression levels from high throughput sequence data: absolute quantitation offers a much sounder basis for determining changes in gene expression level, a measure widely used to determine the consequence of genetic, chemical or physical disturbances in living systems.»

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

Additionally, using RNA - Seq, we determined changes in gene expression levels between the wild - type (WT) and DAXX knock - down (K / D) PC3 cells.

In the search for a defining feature of the Escherichia coli that cause urinary tract infections, comparative transcriptomics and infection models show that infection depends on both the host environment and gene expression levels in the bacteria.