refine.bio
  • Search
      • Normalized Compendia
      • RNA-seq Sample Compendia
  • Docs
  • About
  • My Dataset
github link
Showing
of 308 results
Sort by

Filters

Technology

Platform

accession-icon GSE4870
Expression data from T65H translocation mice
  • organism-icon Mus musculus
  • sample-icon 45 Downloadable Samples
  • Technology Badge Icon Affymetrix Murine Genome U74A Version 2 Array (mgu74av2)

Description

Tissue-specific comparison of gene expression levels in T65H translocation mice, either with or without uniparental duplications of Chrs 7 & 11. Identification of highly differentially expressed transcripts.

Publication Title

Chromosome-wide identification of novel imprinted genes using microarrays and uniparental disomies.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE11789
Expression data from MatDp(dist2) and PatDp(dist2) mice
  • organism-icon Mus musculus
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Comparison of gene expression levels between MatDp(dist2) and PatDp(dist2) mice (newborn whole head). Identification of highly differentially expressed transcripts.

Publication Title

Transcript- and tissue-specific imprinting of a tumour suppressor gene.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE73072
Host gene expression signatures of H1N1, H3N2, HRV, RSV virus infection in adults
  • organism-icon Homo sapiens
  • sample-icon 2886 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

Consider the problem of designing a panel of complex biomarkers to predict a patient's health or disease state when one can pair his or her current test sample, called a target sample, with the patient's previously acquired healthy sample, called a reference sample. As contrasted to a population averaged reference, this reference sample is individualized. Automated predictor algorithms that compare and contrast the paired samples to each other could result in a new generation of test panels that compare to a person's healthy reference to enhance predictive accuracy. This study develops such an individualized predictor and illustrates the added value of including the healthy reference for design of predictive gene expression panels. The objective is to predict each subject's state of infection, e.g., neither exposed nor infected, exposed but not infected, pre-acute phase of infection, acute phase of infection, post-acute phase of infection. Using gene microarray data collected in a large-scale serially sampled respiratory virus challenge study, we quantify the diagnostic advantage of pairing a person's baseline reference with his or her target sample.

Publication Title

An individualized predictor of health and disease using paired reference and target samples.

Sample Metadata Fields

Specimen part, Subject, Time

View Samples
accession-icon GSE71764
Expression data from Arabidopsis during de-etiolation
  • organism-icon Arabidopsis thaliana
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

Arabidopsis fc2-1 mutants fail to properly de-etiolate after a prolonged period in the dark. Our goal was to monitor whole genome expression during the first 2 hours of de-etiolation to determine the cuase of this growth arrest.

Publication Title

Ubiquitin facilitates a quality-control pathway that removes damaged chloroplasts.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE4990
Expression profile between mast cells from diabetic prone and diabetic resistant rat strains
  • organism-icon Rattus norvegicus
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome 230 2.0 Array (rat2302)

Description

Abstract

Publication Title

Evidence of a functional role for mast cells in the development of type 1 diabetes mellitus in the BioBreeding rat.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE30550
Temporal expression data from 17 health human subjects before and after they were challenged with live influenza (H3N2/Wisconsin) viruses
  • organism-icon Homo sapiens
  • sample-icon 268 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

The transcriptional responses of human hosts towards influenza viral pathogens are important for understanding virus-mediated immunopathology. Despite great advances gained through studies using model organisms, the complete temporal host transcriptional responses in a natural human system are poorly understood. In a human challenge study using live influenza (H3N2/Wisconsin) viruses, we conducted a clinically uninformed (unsupervised) factor analysis on gene expression profiles and established an ab initio molecular signature that strongly correlates to symptomatic clinical disease. This is followed by the identification of 42 biomarkers whose expression patterns best differentiate early from late phases of infection. In parallel, a clinically informed (supervised) analysis revealed over-stimulation of multiple viral sensing pathways in symptomatic hosts and linked their temporal trajectory with development of diverse clinical signs and symptoms. The resultant inflammatory cytokine profiles were shown to contribute to the pathogenesis because their significant increase preceded disease manifestation by 36 hours. In subclinical asymptomatic hosts, we discovered strong transcriptional regulation of genes involved in inflammasome activation, genes encoding virus interacting proteins, and evidence of active anti-oxidant and cell-mediated innate immune response. Taken together, our findings offer insights into influenza virus-induced pathogenesis and provide a valuable tool for disease monitoring and management in natural environments.

Publication Title

Temporal dynamics of host molecular responses differentiate symptomatic and asymptomatic influenza a infection.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE55627
Microglial response to A and prostaglandin-E2 EP4 receptor activation
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

A persistent and non-resolving inflammatory response to accumulating A peptide species is a cardinal feature in the development of Alzheimer's disease (AD). In response to accumulating A peptide species, microglia, the innate immune cells of the brain, generate a toxic inflammatory response that accelerates synaptic and neuronal injury. Many pro-inflammatory signaling pathways are linked to progression of neurodegeneration. However, endogenous anti-inflammatory pathways capable of suppressing A-induced inflammation represent a relatively unexplored area.

Publication Title

Suppression of Alzheimer-associated inflammation by microglial prostaglandin-E2 EP4 receptor signaling.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE18388
Microarray Analysis of Space-flown Murine Thymus Tissue
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Microarray Analysis of Space-flown Murine Thymus Tissue Reveals Changes in Gene Expression Regulating Stress and Glucocorticoid Receptors. We used microarrays to detail the gene expression of space-flown thymic tissue and identified distinct classes of up-regulated genes during this process. We report here microarray gene expression analysis in young adult C57BL/6NTac mice at 8 weeks of age after exposure to spaceflight aboard the space shuttle (STS-118) for a period of 13 days. Upon conclusion of the mission, thymus lobes were extracted from space flown mice (FLT) as well as age- and sex-matched ground control mice similarly housed in animal enclosure modules (AEM). mRNA was extracted and an automated array analysis for gene expression was performed. Examination of the microarray data revealed 970 individual probes that had a 1.5 fold or greater change. When these data were averaged (n=4), we identified 12 genes that were significantly up- or down-regulated by at least 1.5 fold after spaceflight (p0.05). Together, these data demonstrate that spaceflight induces significant changes in the thymic mRNA expression of genes that regulate stress, glucocorticoid receptor metabolism, and T cell signaling activity. These data explain, in part, the reported systemic compromise of the immune system after exposure to the microgravity of space.

Publication Title

Microarray analysis of spaceflown murine thymus tissue reveals changes in gene expression regulating stress and glucocorticoid receptors.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE101602
Term Amniotic Fluid: An Unexploited Reserve of Mesenchymal Stromal Cells for Reprogramming and Potential Cell Therapy Applications
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.1 ST Array (hugene11st)

Description

Mesenchymal stromal cells (MSC) are currently being evaluated in numerous preclinical and clinical cell-based therapy studies. Furthermore, there is an increasing interest in exploring alternative uses of these cells in disease modelling, pharmaceutical screening and regenerative medicine by applying reprogramming technologies. However, the limited availability of MSCs from various sources, restricts their use. Term amniotic fluid has been proposed as an alternative source of MSCs. Previously, only low volumes of term fluid and its cellular constituents have been collected, and current knowledge of the MSCs derived from this fluid is limited. In this study, we collected amniotic fluid at term using a novel collection system and evaluated amniotic fluid MSC content and their characteristics, including their feasibility to undergo cellular reprogramming.

Publication Title

Term amniotic fluid: an unexploited reserve of mesenchymal stromal cells for reprogramming and potential cell therapy applications.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE18972
E. coli BW25113 frdC vs. E. coli BW25113 HW2
  • organism-icon Escherichia coli
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix E. coli Genome 2.0 Array (ecoli2)

Description

Glycerol is an attractive feedstock for biofuels since it accumulates as a byproduct during biodiesel operations; hence, it is interesting to consider converting glycerol to hydrogen using the formate hydrogen lyase system of Escherichia coli which converts pyruvate to hydrogen. Starting with Escherichia coli BW25113 frdC that lacks fumarate reductase to eliminate the negative effect of accumulated hydrogen on glycerol fermentation and by using both adaptive evolution and chemical mutagenesis combined with a selection method based on increased growth on glycerol, we obtained an improved strain, HW2, that produces 20-fold more hydrogen in glycerol medium (0.68 mmol/L/h) compared to that of frdC mutant. HW2 also grows 5-fold faster (0.25 1/h) than BW25113 frdC on glycerol, so it achieves a reasonable growth rate. Corroborating the increase in hydrogen production, glycerol dehydrogenase activity in HW2 increased 4-fold compared to BW25113 frdC. In addition, a whole-transcriptome study revealed that several pathways that would decrease hydrogen yields were repressed in HW2 (fbp, focA, and gatYZ) while a beneficial pathway, eno which encodes enolase was induced.

Publication Title

An evolved Escherichia coli strain for producing hydrogen and ethanol from glycerol.

Sample Metadata Fields

No sample metadata fields

View Samples
...

refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

fund-icon Fund the CCDL

Developed by the Childhood Cancer Data Lab

Powered by Alex's Lemonade Stand Foundation

Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

BSD 3-Clause LicensePrivacyTerms of UseContact