Sentences with phrase «gene expression networks»

Researchers will use GTEx data to follow up on findings from genome - wide association studies and as a resource for the general study of gene expression networks.

This highly controlled residential study showed large salutary changes in gene expression networks due to the vacation effect, common to all groups.

Aug. 8, 2017 — Using bioinformatics approaches, Vanderbilt investigators have identified gene expression networks that are deregulated in mouse and human stomach cancers.

Highly coordinated gene expression networks ultimately produce all traits.

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.

Scientists performed an integrative transcriptomic analysis, comparing gene expression networks across all three groups of participants and finding unique molecular profiles and pathway enrichment patterns.

Not exact matches

Often, the genes of the new are present in the body of the old — they are the ideas, the social movements, the fair food networks that start life on the innovative edge, the social fringe, and move towards the middle where they give expression to the new systems that grows out of the old.

Finally, the team identified a network of genes in these regions that exhibit changes in expression when the normal boost from serotonin is lacking, and these changes depended on how long the drug was given.

Nucleic acid and protein sequences, as well as three - dimensional structures of proteins, are frequently the objects of study, but gene expression as well as the simulation of pathways and biochemical networks are attracting more and more attention.

It is a crucial network in the nucleus, providing mechanical support to the nucleus and also regulating gene expression by making some areas of the genome less or more available to be transcribed into messenger RNA.

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.

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.

«New dynamic statistical model follows gene expressions over time: Future applications could range from fMRI data to social networks and more.»

Researchers at Carnegie Mellon University have developed a new dynamic statistical model to visualize changing patterns in networks, including gene expression during developmental periods of the brain.

The enzyme that demethylates histones has been identified, adding another component to the regulatory network that controls gene expression.

By evaluating DNA methylation, the researchers discovered differences in gene networks and gene expression linked to the central nervous system and interactions with HIV that appeared uniquely in monocytes of HIV infected study participants with cognitive impairment.

Amongst others, Dr. Sonntag's work has contributed to developing a cell therapy for Parkinson's disease (PD), and to understanding a role of dysregulated gene and miRNA expression networks in PD and schizophrenia, or dopaminergic and adrenergic receptors in hedonic and impulsive behavior.

Then, methods for reconstructing gene regulatory networks from gene expression data will be looked.

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(1940 ---RRB- Gauer - Henry reflex gauge boson gauge theory gauss (unit) Gauss, Carl Friedrich (1777 — 1855) Gaussian distribution Gay - Lussac, Joseph Louis (1778 — 1850) GCOM (Global Change Observing Mission) Geber (c. 720 — 815) gegenschein Geiger, Hans Wilhelm (1882 — 1945) Geiger - Müller counter Giessler tube gel gelatin Gelfond's theorem Gell - Mann, Murray (1929 ---RRB- GEM «gemination,» of martian canals Geminga Gemini (constellation) Gemini Observatory Gemini Project Gemini - Titan II gemstone gene gene expression gene mapping gene pool gene therapy gene transfer General Catalogue of Variable Stars (GCVS) general precession general theory of relativity generation ship generator Genesis (inflatable orbiting module) Genesis (sample return probe) genetic code genetic counseling genetic disorder genetic drift genetic engineering genetic marker genetic material genetic pool genetic recombination genetics GENETICS AND HEREDITY Geneva Extrasolar Planet Search Program genome genome, interstellar transmission of genotype gentian violet genus geoboard geode geodesic geodesy geodesy satellites geodetic precession Geographos (minor planet 1620) geography GEOGRAPHY Geo - IK geologic time geology GEOLOGY AND PLANETARY SCIENCE geomagnetic field geomagnetic storm geometric mean geometric sequence geometry GEOMETRY geometry puzzles geophysics GEOS (Geodetic Earth Orbiting Satellite) Geosat geostationary orbit geosynchronous orbit geosynchronous / geostationary transfer orbit (GTO) geosyncline Geotail (satellite) geotropism germ germ cells Germain, Sophie (1776 — 1831) German Rocket Society germanium germination Gesner, Konrad von (1516 — 1565) gestation Get Off the Earth puzzle Gettier problem geyser g - force GFO (Geosat Follow - On) GFZ - 1 (GeoForschungsZentrum) ghost crater Ghost Head Nebula (NGC 2080) ghost image Ghost of Jupiter (NGC 3242) Giacconi, Riccardo (1931 ---RRB- Giacobini - Zinner, Comet (Comet 21P /) Giaever, Ivar (1929 ---RRB- giant branch Giant Magellan Telescope giant molecular cloud giant planet giant star Giant's Causeway Giauque, William Francis (1895 — 1982) gibberellins Gibbs, Josiah Willard (1839 — 1903) Gibbs free energy Gibson, Edward G. (1936 ---RRB- Gilbert, William (1544 — 1603) gilbert (unit) Gilbreath's conjecture gilding gill gill (unit) Gilruth, Robert R. (1913 — 2000) gilsonite gimbal Ginga ginkgo Giotto (ESA Halley probe) GIRD (Gruppa Isutcheniya Reaktivnovo Dvisheniya) girder glacial drift glacial groove glacier gland Glaser, Donald Arthur (1926 — 2013) Glashow, Sheldon (1932 ---RRB- glass GLAST (Gamma - ray Large Area Space Telescope) Glauber, Johann Rudolf (1607 — 1670) glaucoma glauconite Glenn, John Herschel, Jr. (1921 ---RRB- Glenn Research Center Glennan, T (homas) Keith (1905 — 1995) glenoid cavity glia glial cell glider Gliese 229B Gliese 581 Gliese 67 (HD 10307, HIP 7918) Gliese 710 (HD 168442, HIP 89825) Gliese 86 Gliese 876 Gliese Catalogue glioma glissette glitch Global Astrometric Interferometer for Astrophysics (GAIA) Global Oscillation Network Group (GONG) Globalstar globe Globigerina globular cluster globular proteins globule globulin globus pallidus GLOMR (Global Low Orbiting Message Relay) GLONASS (Global Navigation Satellite System) glossopharyngeal nerve Gloster E. 28/39 glottis glow - worm glucagon glucocorticoid glucose glucoside gluon Glushko, Valentin Petrovitch (1908 — 1989) glutamic acid glutamine gluten gluteus maximus glycerol glycine glycogen glycol glycolysis glycoprotein glycosidic bond glycosuria glyoxysome GMS (Geosynchronous Meteorological Satellite) GMT (Greenwich Mean Time) Gnathostomata gneiss Go Go, No - go goblet cell GOCE (Gravity field and steady - state Ocean Circulation Explorer) God Goddard, Robert Hutchings (1882 — 1945) Goddard Institute for Space Studies Goddard Space Flight Center Gödel, Kurt (1906 — 1978) Gödel universe Godwin, Francis (1562 — 1633) GOES (Geostationary Operational Environmental Satellite) goethite goiter gold Gold, Thomas (1920 — 2004) Goldbach conjecture golden ratio (phi) Goldin, Daniel Saul (1940 ---RRB- gold - leaf electroscope Goldstone Tracking Facility Golgi, Camillo (1844 — 1926) Golgi apparatus Golomb, Solomon W. 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Green, Thomas Hill (1836 — 1882) green algae Green Bank Green Bank conference (1961) Green Bank Telescope green flash greenhouse effect greenhouse gases Green's theorem Greg, Percy (1836 — 1889) Gregorian calendar Grelling's paradox Griffith, George (1857 — 1906) Griffith Observatory Grignard, François Auguste Victor (1871 — 1935) Grignard reagent grike Grimaldi, Francesco Maria (1618 — 1663) Grissom, Virgil (1926 — 1967) grit gritstone Groom Lake Groombridge 34 Groombridge Catalogue gross ground, electrical ground state ground - track group group theory GROUPS AND GROUP THEORY growing season growth growth hormone growth hormone - releasing hormone growth plate Grudge, Project Gruithuisen, Franz von Paula (1774 — 1852) Grus (constellation) Grus Quartet (NGC 7552, NGC 7582, NGC 7590, and NGC 7599) GSLV (Geosynchronous Satellite Launch Vehicle) g - suit G - type asteroid Guericke, Otto von (1602 — 1686) guanine Guiana Space Centre guidance, inertial Guide Star Catalog (GSC) guided missile guided missiles, postwar development Guillaume, Charles Édouard (1861 — 1938) Gulf Stream (ocean current) Gulfstream (jet plane) Gullstrand, Allvar (1862 — 1930) gum Gum Nebula gun metal gunpowder Gurwin Gusev Crater gut Gutenberg, Johann (c. 1400 — 1468) Guy, Richard Kenneth (1916 ---RRB- guyot Guzman Prize gymnosperm gynecology gynoecium gypsum gyrocompass gyrofrequency gyropilot gyroscope gyrostabilizer Gyulbudagian's Nebula (HH215)

Additionally, the interpretation of levels of change in gene expression in isolation, without the additional statistical rigor provided by the concomitant analysis of ontological interaction networks, may severely limit critical insights into relevant biologic processes.

Thus, interactome hubs such as NR1 may exhibit low levels of change in individual gene expression following hypoxia, but, based on analysis of interaction networks, are likely to play an important role in regulating the biologic response.

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

The NIH Common Fund's Library of Integrated Network - based Cellular Signatures (LINCS) program aims to create a network - based understanding of biology by cataloging changes in gene expression and other cellular processes that occur when cells are exposed to a variety of perturbing Network - based Cellular Signatures (LINCS) program aims to create a network - based understanding of biology by cataloging changes in gene expression and other cellular processes that occur when cells are exposed to a variety of perturbing network - based understanding of biology by cataloging changes in gene expression and other cellular processes that occur when cells are exposed to a variety of perturbing agents.

He group is also interested in high throughput gene expression data analysis, especially using Bayesian network (BN) approaches.

Now researchers at UC San Francisco have taken the first step toward a comprehensive atlas of gene expression in cells across the developing human brain, making available new insights into how specific cells and gene networks contribute to building this most complex of organs, and serving as a resource for researchers around the world to study the interplay between these genetic programs and neurodevelopmental disorders such as autism, intellectual disability and schizophrenia.

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.

ARNIE is an online database that integrates the extracellular protein interaction network generated in our lab using AVEXIS technology with spatiotemporal expression patterns for all genes in the network.

We have developed new BN algorithms and tools for analysis of gene interaction networks using high throughput gene expression data.

In addition, we explored the differential genes expressions between day and night in the presence of high calcium concentration seawater in order to identify the presence of networks of regulatory genes in a basal metazoan.

At any given instant it can be argued that the cell is in a «state» defined by its components — their concentrations and locations, the interactions between components — that are modulated in space and time, and the complex circuitry — that involves a large number of interacting networks and a snapshot of the dynamical processes — such as gene expression, cell cycle, transport of components, etc..

The 4D Nucleome Network, funded by the National Institutes of Health, and the 4D Genome Project, funded by the European Research Council, are identifying a vocabulary of DNA structural elements and relating how that structure impacts gene expression.

We focus on developing computational methods and tools for (a) analyzing large - scale gene expression data related to human cancer in search for gene markers and disease sub-categories, (b) identifying regulatory elements such as miRNA precursors and their targets in whole genomes of plants and mammals, (c) building theoretical models of gene regulatory networks.

Using bioinformatics approaches, they identified transcription (gene expression) networks that were consistently deregulated in both mouse and human lesions.

We also identified a «meditation effect» within the regular meditator group, characterized by a distinct network of genes with cellular functions that may be relevant to healthy aging, and this network was associated with increased expression of a number of telomere maintenance pathway genes and an increase in measured telomerase enzymatic activity.

The application of transgenesis and other genetic methods - in conjunction with total genome sequence and database information on gene expression patterns, morphological changes during development, and mutant phenotypes - should significantly enhance our ability to unravel the multilayered networks that control gene expression and differentiation.

Members of the TCGA Research Network identified and characterized four glioblastoma subtypes using gene expression, somatic mutation, and copy number data.

«We found that genes associated with successful FDA - approved drugs have several properties at the network, sequence, and tissue - expression levels that significantly distinguish them from other human genes,» the authors conclude.

We are currently testing the hypothesis that these transcription factors form a genomic regulatory network, and disruption of that network by mutation destabilizes gene expression programs, contributing to malignancy.

In small cell lung cancer, starting from bioinformatics analyses of large gene expression datasets, we clustered subsets of co-expressed gene modules, derived networks of transcription factors and simulated their dynamics using logic - based mathematical modeling.

«Our network has the property that when there are low levels of the primary regulators — PU.1 or C / EBPα — there is a mixed lineage pattern of gene expression,» said Singh.

We are particularly interested in how miRNAs can generate thresholds in target gene expression and mediate feedforward and feedback loops in gene networks.

We are particularly interested in how cells use gene networks to make robust decisions even in the presence of significant fluctuations in gene expression.

Comparative RNA - Seq based dissection of the regulatory networks and environmental stimuli underlying Vibrio parahaemolyticus gene expression during infection.

15/3: 30 Tissue - specific transcriptome - wide networks reflect joint regulation of alternative splicing and gene expression.

Her research interests are focused on the reconstruction of cell response networks from integrated gene and protein expression data to enable predictive mechanistic modeling of disease and toxicity pathways.

Recent studies of the ES cell transcriptome and epigenome have revealed networks of co-regulated transcription factors that maintain pluripotency and suppress the expression of genes associated with particular differentiation lineages [2].

Current research is looking closely at the interactions of different gene expressions and protein networks, within normal versus neoplastic cells.