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accession-icon GSE41926
Gene expression analysis of Pseudomonas aeruginosa wild type, delta-gbdR, and delta-plcHR deletion mutants
  • organism-icon Pseudomonas aeruginosa pao1
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Pseudomonas aeruginosa Array (paeg1a)

Description

Pseudomonas aeruginosa is a virulent opportunistic pathogen responsible for high morbity in COPD, burns , implanted medical devices and cystic fibrosis.

Publication Title

Anr and its activation by PlcH activity in Pseudomonas aeruginosa host colonization and virulence.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE9630
Expression data from mouse liver
  • organism-icon Mus musculus
  • sample-icon 59 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Exposure to high levels of arsenic in drinking water is associated with several types of cancers including lung, bladder and skin, as well as vascular disease and diabetes. Drinking water standards are based primarily on epidemiology and extrapolation from higher dose experiments, rather than measurements of phenotypic changes associated with chronic exposure to levels of arsenic similar to the current standard of 10ppb, and little is known about the difference between arsenic in food as opposed to arsenic in water. Measurement of phenotypic changes at low doses may be confounded by the effect of laboratory diet, in part because of trace amounts of arsenic in standard laboratory chows, but also because of broad metabolic changes in response to the chow itself. Finally, this series contrasts 8hr, 1mg/kg injected arsenic with the various chronic exposures, and also contrasts the acute effects of arsenic, dexamethasone or their combination. Male C57BL/6 mice were fed on two commercially available laboratory diets (LRD-5001 and AIN-76A) were chronically exposed, through drinking water or food, to environmentally relevant concentrations of sodium arsenite, or acutely exposed to dexamethasone.

Publication Title

Laboratory diet profoundly alters gene expression and confounds genomic analysis in mouse liver and lung.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE11056
Expression data from mouse lung
  • organism-icon Mus musculus
  • sample-icon 55 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Exposure to high levels of arsenic in drinking water is associated with several types of cancers including lung, bladder and skin, as well as vascular disease and diabetes. Drinking water standards are based primarily on epidemiology and extrapolation from higher dose experiments, rather than measurements of phenotypic changes associated with chronic exposure to levels of arsenic similar to the current standard of 10ppb, and little is known about the difference between arsenic in food as opposed to arsenic in water. Measurement of phenotypic changes at low doses may be confounded by the effect of laboratory diet, in part because of trace amounts of arsenic in standard laboratory chows, but also because of broad metabolic changes in response to the chow itself. Finally, this series contrasts 8hr, 1mg/kg injected arsenic with the various chronic exposures, and also contrasts the acute effects of arsenic, dexamethasone or their combination. Male C57BL/6 mice were fed on two commercially available laboratory diets (LRD-5001 and AIN-76A) were chronically exposed, through drinking water or food, to environmentally relevant concentrations of sodium arsenite, or acutely exposed to dexamethasone.

Publication Title

Chronic exposure to arsenic in the drinking water alters the expression of immune response genes in mouse lung.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP095168
Identification of Transcripts Involved in Neural Tube Closure Using RNA-sequencing
  • organism-icon Danio rerio
  • sample-icon 36 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

The transcriptome of zebrafish embryos treated with a Nodal signaling inhibitor at sphere stage, which causes neural tube defects, is compared to those treated at 30% epiboly, which does not. Overall design: Transcriptomic analysis of differential gene expression of key developmental pathways under differing inhibitory treatments.

Publication Title

Identification of transcripts potentially involved in neural tube closure using RNA sequencing.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE34465
Expression data from periphereal blood lymphocytes of metastatic renal cell carcinoma patients pre and post therapy as well as 9 healthy controls
  • organism-icon Homo sapiens
  • sample-icon 39 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Gene expression of periphereal blood lymphocytes (PBLs) of patients with metastatic renal cell carcinoma pre and post immunotherapy was accessed and pre therapy gene expression was compared to PBL gene expression of healthy volunteers

Publication Title

Gene expression profile of peripheral blood lymphocytes from renal cell carcinoma patients treated with IL-2, interferon-α and dendritic cell vaccine.

Sample Metadata Fields

Specimen part, Disease, Disease stage

View Samples
accession-icon GSE30439
Exposure of cystic fibrosis bronchial epithelial cells (CFBE 41 o-) to Pseudomonas aeruginosa (PA01) biofilms
  • organism-icon Homo sapiens
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

In the clinical setting, mutations in the CFTR gene enhance the inflammatory response to P. aeruginosa (PA01) infection, but measurements of the inflammatory response to pathogen stimulation by isolated airway epithelia can yield variable results. In this series, we exposed CFBE41o- cells over-expressing F508/F508 CFTR and CFBE41o- cells rescued with wt-CFTR to P. aeruginosa biofilms. P. aeruginosa elicited a more robust increase in cytokine and chemokine expression (e.g., IL-8, CXCL2, CXCL3, CXCR4 and TNF-) in CFBE-wt-CFTR cells compared to CFBE-F508-CFTR cells. These results demonstrate that CFBE41o- cells complemented with wt-CFTR mount a more robust inflammatory response to P. aeruginosa than CFBE41o- F508/F508-CFTR cells.

Publication Title

Does the F508-CFTR mutation induce a proinflammatory response in human airway epithelial cells?

Sample Metadata Fields

Specimen part

View Samples
accession-icon SRP077289
Using RNA Seq to validate transcriptional profile data obtained by Nanostring analysis
  • organism-icon Pseudomonas aeruginosa
  • sample-icon 16 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

Purpose : The goal of this study was to use RNA Seq to validate transcriptional data of two clinical isolates focussing on a subset of 74 transcript that were selected specifically for Nanostring analysis. Methods : mRNA profiles were generated for the clinical isolates FRD1 and CI224_M, in duplicate, by deep sequencing. Strains were grown for 8 hours in LB medium at 37C prior to RNA harvest. Ribosomal RNA was removed using the Ribi-Zero rRNA Removal Kit (Epicentre). mRNA reads were trimmed and mapped to the PAO1 NC_002516 reference genome from NCBI using the ClC Genomics Workbench platform and defaut parameters. Overall design: mRNA profiles of liquid cultures grown for 8 hours in LB at 37C were generated for P. aeruginosa clinical isolates FRD1 and CI224_M, each in duplicate, by deep sequencing using Illumina NextSeq.

Publication Title

Use of a Multiplex Transcript Method for Analysis of Pseudomonas aeruginosa Gene Expression Profiles in the Cystic Fibrosis Lung.

Sample Metadata Fields

Disease, Subject

View Samples
accession-icon GSE5462
Letrozole (Femara) early response to treatment
  • organism-icon Homo sapiens
  • sample-icon 113 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

In the present investigation, we have exploited the opportunity provided by neoadjuvant treatment of a group of postmenopausal women with large operable or locally advanced breast cancer (in which therapy is given with the primary tumour remaining within the breast) to take sequential biopsies of the same cancers before and after 10-14 days treatment with letrozole. RNA extracted from the biopsies has been subjected to Affymetrix microarray analysis and the data from paired biopsies interrogated to discover genes whose expression is most influenced by oestrogen deprivation.

Publication Title

Changes in breast cancer transcriptional profiles after treatment with the aromatase inhibitor, letrozole.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE97
Large-scale analysis of the mouse transcriptome
  • organism-icon Mus musculus
  • sample-icon 88 Downloadable Samples
  • Technology Badge Icon Affymetrix Murine Genome U74A Array (mgu74a)

Description

High-throughput gene expression profiling has become an important tool for investigating transcriptional activity in a variety of biological samples. To date, the vast majority of these experiments have focused on specific biological processes and perturbations. Here, we have generated and analyzed gene expression from a set of samples spanning a broad range of biological conditions. Specifically, we profiled gene expression from 91 human and mouse samples across a diverse array of tissues, organs, and cell lines. Because these samples predominantly come from the normal physiological state in the human and mouse, this dataset represents a preliminary, but substantial, description of the normal mammalian transcriptome. We have used this dataset to illustrate methods of mining these data, and to reveal insights into molecular and physiological gene function, mechanisms of transcriptional regulation, disease etiology, and comparative genomics. Finally, to allow the scientific community to use this resource, we have built a free and publicly accessible website (http://biogps.gnf.org) that integrates data visualization and curation of current gene annotations.

Publication Title

Large-scale analysis of the human and mouse transcriptomes.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE96
Large-scale analysis of the human transcriptome
  • organism-icon Homo sapiens
  • sample-icon 85 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U95A Array (hgu95a)

Description

High-throughput gene expression profiling has become an important tool for investigating transcriptional activity in a variety of biological samples. To date, the vast majority of these experiments have focused on specific biological processes and perturbations. Here, we have generated and analyzed gene expression from a set of samples spanning a broad range of biological conditions. Specifically, we profiled gene expression from 91 human and mouse samples across a diverse array of tissues, organs, and cell lines. Because these samples predominantly come from the normal physiological state in the human and mouse, this dataset represents a preliminary, but substantial, description of the normal mammalian transcriptome. We have used this dataset to illustrate methods of mining these data, and to reveal insights into molecular and physiological gene function, mechanisms of transcriptional regulation, disease etiology, and comparative genomics. Finally, to allow the scientific community to use this resource, we have built a free and publicly accessible website (http://expression.gnf.org) that integrates data visualization and curation of current gene annotations.

Publication Title

Large-scale analysis of the human and mouse transcriptomes.

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

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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.

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