Sentences with phrase «of gene expression data»

In the current study, the researchers used infradian cyclic locomotor activity in the mutant mice as a proxy for mood - associated changes, and examined their molecular basis in the brain by conducting prediction analyses of the gene expression data.

In the current study, prediction analysis of gene expression data was implemented in order to identify the genes that are most useful to determine the state of cyclic changes in locomotor activity.

At the nucleic acid level, understanding the precise regulation of genes through analysis of gene expression data will be of utmost importance.

«For several years the potential for the use of gene expression data in research and clinical applications has been underappreciated due to the inconsistency of the data coming from the various types of equipment.

Scientists from the Biogerontology Research Foundation (BGRF), a UK - based charity founded to support aging research and address the challenges of a rapidly aging population, propose a new concept for signalome - wide analysis of changes in intracellular pathways, called OncoFinder, which allows for accurate and robust cross-platform analysis of gene expression data.

Not exact matches

«Together, our data strongly suggest that cutaneous gene therapy with inducible expression of GLP1 can be used for the treatment and prevention of diet - induced obesity and pathologies,» the authors wrote.

The challenge is substantial — the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus repository (GEO) alone contains 80,985 public datasets, spanning hundreds of tissue types in thousands of organisms — and the rapid growth in data makes it difficult for journals or data repositories to «police» whether datasets that should be made publicly available actually are.

«We used the Allen Human Brain Atlas data to quantify how consistent the patterns of expression for various genes are across human brains, and to determine the importance of the most consistent and reproducible genes for brain function.»

«It is exciting to find a correlation between brain circuitry and gene expression by combining high quality data from these two large - scale projects,» says David Van Essen, Ph.D., professor at Washington University in St. Louis and a leader of the Human Connectome Project.

Until now, the data and test results for this ongoing work have all come from preexisting, online digital data sets of gene expression from patients with different kinds of infections — not from current patients.

In this study, a team led by Panos N. Papapanou, DDS, PhD, professor and chair of oral, diagnostic and rehabilitation sciences at the College of Dental Medicine at CUMC, «reverse - engineered» the gene expression data to build a map of the genetic interactions that lead to periodontitis and identify individual genes that appear to have the most influence on the disease.

Our data indicate that gene expression is coordinately regulated, such that states of increased proliferation are associated with widespread reductions in the 3 ′ UTR - based regulatory capacity of mRNAs.

The data are already being used to improve gene information and expression on VectorBase, a National Institute of Allergy and Infectious Diseases resource center for the scientific community.

Biomolecular model based on the gene expression data analyses support the reduction of glucose molecules (blue gradient) and acid buildup (gold gradient) proposed to occur in the boundary layer around the cell.

Using breast cancer patient data taken from The Cancer Genome Atlas, molecular biologists Curt M. Horvath and Robert W. Tell used powerful computational and bioinformatics techniques to detect patterns of gene expression in two cancer subtypes.

This new gene expression data therefore provides additional evidence that the altered behavior of bacteria in space results from decreased gravity driving reduced extracellular transport of molecules.

Computational genomics includes: bio-sequence analysis, gene expression data analysis, phylogenetic analysis, and more specifically pattern recognition and analysis problems such as gene finding, motif finding, gene function prediction, fusion of sequence and expression information, and evolutionary models.

Epiviz implements multiple visualization methods for location - based data (such as genomic regions of interest) and feature - based data (such as gene expression), using interactive data visualization techniques not available in web - based genome browsers.

The researchers named the method after a fish famous for swimming upstream because it employs an algorithm that can estimate the effect of biases and the expression level of genes as experimental data streams by.

Using clinical, genetic, and gene expression data as filters to distinguish genes whose copy number alteration causes cancer from those for whom copy number changes are incidental, the team whittled down their list from 14,000 to a more manageable number, each of which they systematically tested using genetic experiments in animals.

To study gene expression, they then examined RNA sequencing data from 25 of the biliary - phenotype cancers and 44 hepatocellular cancers.

One important level of information discovered in their data was a record of past gene expression.

MEGENA (for Multiscale Embedded Gene Co-expression Network Analysis) projects gene expression data onto a three dimensional sphere, allowing scientists to study hierarchical organization patterns in complex networks that are characteristic of diseases such as cancer, obesity, and AlzheimeGene Co-expression Network Analysis) projects gene expression data onto a three dimensional sphere, allowing scientists to study hierarchical organization patterns in complex networks that are characteristic of diseases such as cancer, obesity, and Alzheimegene expression data onto a three dimensional sphere, allowing scientists to study hierarchical organization patterns in complex networks that are characteristic of diseases such as cancer, obesity, and Alzheimer's.

The second tool, SuperExactTest, establishes the very first theoretical framework for assessing the statistical significance of multi-set intersections and enables users to compare very large sets of data, such as gene sets produced from genome - wide association studies (GWAS) and differential expression analysis.

Andrechek's federally funded study looked at mice containing all subtypes and compared the makeup of the rodent tumors and the way the genes acted, known as gene expression, to human tumor data.

Toxicologist Craig Harris of the University of Michigan, Ann Arbor, who has studied thalidomide's effects on gene expression, says that the new data are consistent with some theories of the drug's action, however.

HDNetDB allows users to obtain, visualise and prioritise molecular interaction networks using Huntington's disease - related gene expression and other types of data obtained from human samples and other sources.

The project was based on gene expression data from the modENCODE project, which aims to provide the scientific community with a comprehensive encyclopedia of functional elements of the genome of model organisms.

Microarrays allow researchers to acquire data about expression levels of thousands of genes at one fell swoop.

For instance, the National Center for Biotechnology Information's public repository of gene - expression data, GEO, now contains 392,000 microarray experiments.

«It is also possible that these data will reveal that some previously identified disease - associated sequence variants actually fall within a formerly unrecognized primary miRNA gene, thereby raising the possibility that such variants may influence expression of the encoded miRNA,» Mendell said.

The accumulation of adipose tissue macrophages in direct proportion to adipocyte size and body mass may explain the coordinated increase in expression of genes encoding macrophage markers observed in our microarray expression data.

The expression of mRNA for factors involved in promoting mitochondrial biogenesis, including the transcription factor Ppard, the PPARδ coactivator Pgc - 1α, and citrate synthase was greater in gastrocnemius muscles from IL - 15Rα — KO relative to B6129 control (Figure 5C); however, levels of these genes were unchanged in spleen and kidney (data not shown).

Evan Paull, a graduate student in Stuart's lab at UC Santa Cruz (now at Columbia University), led the computational analyses, which involved integrating the phosphoproteomic data with genomic and gene expression datasets to provide a unified view of the activated signaling pathways in late stage prostate cancer.

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).

These data demonstrate that variations in continuous quantitative traits such as body mass, adipocyte size, and BMI are correlated with quantitative variations in the expression of genes.

«We analyzed dozens of variants of this gene and quantitatively measured expression in about 1,000 embryos, creating a quantitative data set that could be used to train mathematical models, utilizing parameter optimization,» Arnosti said.

It contains data on the electrical properties of about 300 cortical neurons taken from 36 patients and 3D reconstructions of 100 of those cells, plus gene expression data from 16,000 neurons from three other patients.

Integration of our genomics, genetics, cell biological and biochemical approaches, supported with computational data mining, provides insight into the multi-layered gene expression networks and of regulatory strategies orchestrating biological processes.

The atlas now also includes RNA transcript data for 27 of these organ - specific tissues using next generation sequencing, providing a tissue distribution map of both protein and gene expression.

(Mixture - of - Isoforms) for isoform quantitation using RNA - Seq is a probabilistic framework that quantitates the expression level of alternatively spliced genes from RNA - Seq data, and identifies differentially regulated isoforms or exons across samples.

The authors next took 997 tumors in the discovery set, integrated copy number and gene expression data, and performed clustering analyses to identify subgroups of tumors with distinct features and clinical outcomes.

A research team, led by Chao Cheng, Ph.D., Assistant Professor in the Department of Genetics at The Geisel School of Medicine at Dartmouth, used gene expression data from breast cancer patients to computationally infer the presence of different types of immune cells.

Most of these were invalidated when challenged with experimental data generated in Smith's laboratory, which measured gene expression of ESCs across 23 different cell culture conditions, all of which maintained pluripotency.

The Human Protein Atlas has reached a major milestone by releasing protein data for more than 80 % of the human protein - coding genes and RNA expression data for more than 90 % of the genes.

«This data allows classification of all human protein - coding genes into those coding for house - hold functions (present in all cells) and those that are tissue - specific genes with highly specialized expression in particular organs and tissues, such as kidney, liver, brain, heart, pancreas.

«We are truly excited about the RNA transcript data and the map of gene expression that we now have for 27 different organ - specific tissues», says Professor Mathias Uhlén, Program Director of the Human Protein Atlas.

James Giovannoni generated the gene expression data through RNA - sequencing and Lukas Mueller provided additional analysis to confirm the quality of the genome assembly.

Garcia - Ojalvo expressed surprise that a network based only on gene expression data could predict, with relative accuracy, the effect of multiple genetic interactions.

Gene Set Enrichment Analysis (GSEA) is a microarray data - mining technique used to determine whether there is coordinated differential expression or «enrichment» in a set of functionally related genes when comparing control and experimental samples [35].