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accession-icon GSE31355
A genome wide methylation map of neuroblastoma cell lines
  • organism-icon Homo sapiens
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Genome-wide promoter methylation analysis in neuroblastoma identifies prognostic methylation biomarkers.

Sample Metadata Fields

Treatment

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accession-icon GSE31229
Neuroblastoma cell lines treated with DAC (2'-deoxy-5-azacytidine), a DNA-methylation inhibitor
  • organism-icon Homo sapiens
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

8 neuroblastoma (NB) cell lines (CLB-GA, IMR-32, SH-SY5Y, N206, CHP-902R, LAN-2, SK-N-AS, SJNB-1) were profiled on the Affymetrix HGU-133plus2,0 platform before and after treatment with DAC (2'-deoxy-5-azacytidine) to investigate the influence on expression after inhibiting DNA-methylation

Publication Title

Genome-wide promoter methylation analysis in neuroblastoma identifies prognostic methylation biomarkers.

Sample Metadata Fields

Treatment

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accession-icon GSE21713
mRNA expression data from primary untreated neuroblastoma tumour samples
  • organism-icon Homo sapiens
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

The miR-17-92 microRNA cluster is often activated in cancer cells, but the identity of its targets remains largely elusive. Here we examined the effects of activation of the entire miR-17-92 cluster on global protein expression in neuroblastoma cells.

Publication Title

The miR-17-92 microRNA cluster regulates multiple components of the TGF-β pathway in neuroblastoma.

Sample Metadata Fields

Specimen part

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accession-icon GSE39966
Expression data from replicating and quiescent liver cells isolated from mice young liver
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

We have developed a new transgenic mouse strain, expressing a CyclinB1-GFP fusion reporter, which marks replicating cells in the S/G2/M phases of the cell cycle to isolate live replicating and quiescent cells from the liver.

Publication Title

A transgenic mouse marking live replicating cells reveals in vivo transcriptional program of proliferation.

Sample Metadata Fields

Age, Specimen part

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accession-icon SRP074850
Systems genetics reveals a transcriptional network associated with susceptibility in the maize-gray leaf spot pathosystem
  • organism-icon Zea mays
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Background: Maize plants developed typical gray leaf spot disease (GLS) symptoms initiating at the lower leaves and progressing to upper leaves through the season. Leaf material was collected at 77 days after planting, at which stage there were a large number of GLS disease necrotic lesions on lower leaves (8% surface area on average determined by digital image analysis), but very few lesions and only at chlorotic stage on leaves above the ear (average of 0.2% lesion surface area). Method:To collect material that reflected a difference between C.zeina infected B73 leaves and control B73 leaf material, samples were collected from two lower GLS infected leaves (second and third leaf internode below ear) , and two upper leaves with minimal GLS symptoms (second and third internode above ear), respectively. The two lower leaves from each plant were pooled prior to RNA extraction, and the two upper leaves from each plant were pooled prior to RNA extraction. Upper and lower leaf samples from three maize B73 plants were subjected to RNA sequencing individually. The three maize plants were selected randomly as one plant per row from three rows of ten B73 plants each. Result: A systems genetics strategy revealed regions on the maize genome underlying co-expression of genes in susceptible and resistance responses, including a set of 100 genes common to the susceptible response of sub-tropical and temperate maize. Overall design: To collect material that reflected a difference between C.zeina infected B73 leaves and control B73 leaf material, samples were collected from two lower GLS infected leaves (second and third leaf internode below ear) , and two upper leaves with minimal GLS symptoms (second and third internode above ear), respectively. The two lower leaves from each plant were pooled prior to RNA extraction, and the two upper leaves from each plant were pooled prior to RNA extraction. Upper and lower leaf samples from three maize B73 plants were subjected to RNA sequencing individually. The three maize plants were selected randomly as one plant per row from three rows of ten B73 plants each.

Publication Title

Systems genetics reveals a transcriptional network associated with susceptibility in the maize-grey leaf spot pathosystem.

Sample Metadata Fields

Subject

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accession-icon GSE49981
Reciprocal transcriptional responses in the interaction between Arabidopsis thaliana and Tetranychus urticae.
  • organism-icon Arabidopsis thaliana
  • sample-icon 28 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

While pathogen-induced immunity is comparatively well characterized, far less is known about plant defense responses to arthropod herbivores. To date, most molecular-genetic studies of plant-arthropod interactions have focused on insects. However, plant-feeding (phytophagous) mites are also pests of diverse plants, and mites induce different patterns of damage to plant tissues than do well-studied insects (e.g., Lepidopteran larvae or aphids). The two-spotted spider mite, Tetranychus urticae, is among the most significant mite pests in agriculture. T. urticae is an extreme generalist that has been documented on a staggering number of plant hosts (more than 1,100), and is renowned for the rapid evolution of pesticide resistance. To understand reciprocal interactions between T. urticae and a plant host at the molecular level, we examined mite herbivory using Arabidopsis thaliana. Despite differences in feeding guilds, we found that transcriptional responses of A. thaliana to mite herbivory generally resembled those observed for insect herbivores. In particular, defense to mites was mediated by jasmonic acid (JA) biosynthesis and signaling. Further, indole glucosinolates dramatically increased mite mortality and development times. Variation in both basal and activated levels of these defense pathways might also explain differences in mite damage and feeding success between A. thaliana accessions. On the herbivore side, a diverse set of genes associated with detoxification of xenobiotics was induced upon exposure to increasing levels of in planta indole glucosinolates. Our findings provide molecular insights into the nature of, and response to, herbivory for a representative of a major class of arthropod herbivores.

Publication Title

Reciprocal responses in the interaction between Arabidopsis and the cell-content-feeding chelicerate herbivore spider mite.

Sample Metadata Fields

Age, Specimen part, Treatment

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accession-icon E-MEXP-2472
Transcription profiling by array of Arabidopsis after growing in dark or light conditions
  • organism-icon Arabidopsis thaliana
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconUNKNOWN, Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

RNA from etiolated seedlings, light-treated seedlings, leaves and flowers was hybridized to ATH1 and AGRONOMICS1 arrays.

Publication Title

AGRONOMICS1: a new resource for Arabidopsis transcriptome profiling.

Sample Metadata Fields

Age, Specimen part

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accession-icon SRP056481
Long-term consequences of chronic fluoxetine exposure on the expression of myelination-related genes in the rat hippocampus
  • organism-icon Rattus norvegicus
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer IIx

Description

To more concretely elucidate the long-term effects of chronic SSRI exposure during adulthood, the long-term consequences of chronic fluoxetine (12 mg/kg) versus vehicle treatment during adulthood (postnatal day (PND) 67-88) on gene expression in the hippocampus were investigated. The study showed that adult chronic fluoxetine exposure causes on the long-term changes in the expression of genes related to, amongst others, myelination Overall design: Comparison of gene expression in hippocampus tissue of fluoxetine and methylcellulose-exposed rats (postnatal day 128). 2 rats pooled per sample, 2 samples per treatment group

Publication Title

Long-term consequences of chronic fluoxetine exposure on the expression of myelination-related genes in the rat hippocampus.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE27720
AMPK stimulation and PGC-1 alpha suppression in peroxisome deficient hepatocytes favor catabolic over anabolic carbohydrate metabolism
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

These arrays contain data from the livers of 10 week old L-Pex5 -/- male mice

Publication Title

Carbohydrate metabolism is perturbed in peroxisome-deficient hepatocytes due to mitochondrial dysfunction, AMP-activated protein kinase (AMPK) activation, and peroxisome proliferator-activated receptor γ coactivator 1α (PGC-1α) suppression.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE9385
Identification of differentially regulated splice variants and novel exons in glial brain tumors using exon arrays
  • organism-icon Homo sapiens
  • sample-icon 42 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)

Description

Aberrant splice variants are involved in the initiation and/or progression of glial brain tumors. We therefore set out to identify splice variants that are differentially expressed between histological subgroups of gliomas. Splice variants were identified using a novel platform that profiles the expression of virtually all known and predicted exons present in the human genome. Exon-level expression profiling was performed on 26 glioblastomas, 22 oligodendrogliomas and 6 control brain samples. Our results demonstrate that Human Exon arrays can identify subgroups of gliomas based on their histological appearance and genetic aberrations. We next used our expression data to identify differentially expressed splice variants. In two independent approaches, we identified 49 and up to 459 exons that are differentially spliced between glioblastomas and oligodendrogliomas a subset of which (47% and 33%) were confirmed by RT-PCR. In addition, exon-level expression profiling also identified >700 novel exons. Expression of ~67% of these candidate novel exons was confirmed by RT-PCR. Our results indicate that exon-level expression profiling can be used to molecularly classify brain tumor subgroups, can identify differentially regulated splice variants and can identify novel exons. The splice variants identified by exon-level expression profiling may help to detect the genetic changes that cause or maintain gliomas and may serve as novel treatment targets.

Publication Title

Identification of differentially regulated splice variants and novel exons in glial brain tumors using exon expression arrays.

Sample Metadata Fields

No sample metadata fields

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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)

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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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