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accession-icon SRP091513
Drosophila melanogaster Infection-regulated Transcriptome
  • organism-icon Drosophila melanogaster
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

A project to identify genes and transcripts regulated by infection in Drosophila melanogaster.

Publication Title

No associated publication

Sample Metadata Fields

Sex, Specimen part, Cell line, Treatment

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accession-icon SRP034567
Mus Musculus Transcriptome or Gene expression
  • organism-icon Mus musculus
  • sample-icon 2 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

RNAseq data from Interleukin-21 contributes to fatal inflammatory disease in the absence of FoxP3+ T regulatory cells

Publication Title

No associated publication

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE11516
Circadian Rhythm of Gene Expression Patterns in Liver of Mouse
  • organism-icon Mus musculus
  • sample-icon 36 Downloadable Samples
  • Technology Badge IconMouseWG-6 V2

Description

Genes encoding the circadian pacemaker in the hypothalamic suprachiasmatic nuclei (SCN) of mammals have recently been identified, but the molecubasis of circadian timing in peripheral tissue is not well understood. We used a bead-based microarray to identify mouse liver transcripts that show circadian cycles of abundance under constant conditions.

Publication Title

Comprehensive analysis of microRNA-mRNA co-expression in circadian rhythm.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE43677
Massive Transcriptional Perturbation in Subgroups of Diffuse Large B-cell Lymphomas
  • organism-icon Homo sapiens
  • sample-icon 71 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Based on the assumption that molecular mechanisms involved in cancerogenesis are characterized by groups of coordinately expressed genes, we developed and validated a novel method for analyzing transcriptional data called Correlated Gene Set Analysis (CGSA). Using 50 extracted gene sets we identified three different profiles of tumors in a cohort of 364 Diffuse large B-cell (DLBCL) and related mature aggressive B-cell lymphomas other than Burkitt lymphoma. The first profile had high level of expression of genes related to proliferation whereas the second profile exhibited a stromal and immune response phenotype. These two profiles were characterized by a large scale gene activation affecting genes which were recently shown to be epigenetically regulated, and which were enriched in oxidative phosphorylation, energy metabolism and nucleoside biosynthesis. The third and novel profile showed only low global gene activation similar to that found in normal B cells but not cell lines. Our study indicates novel levels of complexity of DLBCL with low or high large scale gene activation related to metabolism and biosynthesis and, within the group of highly activated DLBCLs, differential behavior leading to either a proliferative or a stromal and immune response phenotype.

Publication Title

Massive transcriptional perturbation in subgroups of diffuse large B-cell lymphomas.

Sample Metadata Fields

No sample metadata fields

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accession-icon DRP003539
Transcriptome analysis for revealing the process of tumor progression
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer IIx

Description

For revealing the carcinogenesis mechanism leading to malignant alteration at the transcriptome level, we performed mRNA-Seq for mouse tumor samples that were obtained by using a DMBA-TPA two-step experimental carcinogenesis protocol.

Publication Title

No associated publication

Sample Metadata Fields

Disease

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accession-icon E-MEXP-231
Transcription profiling by array of human primary lung adenocarcinomas
  • organism-icon Homo sapiens
  • sample-icon 58 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Gene transcription in a set of 49 human primary lung adenocarcinomas and 9 normal lung tissue samples was examined using Affymetrix GeneChip technology. We aimed to investigate differential gene expression between the two tissue types. A total of 3,442 genes, called the set MAD, were found to be either up- or down-regulated by at least two fold between the two phenotypes. Genes assigned to a particular gene ontology term were found, in many cases, to be significantly unevenly distributed between the genes in and outside MAD. Terms that were overrepresented in MAD included functions directly implicated in cancer cell metabolism. Based on their functional roles and expression profiles, genes in MAD were grouped into likely co-regulated gene sets.

Publication Title

Conserved transcription factor binding sites of cancer markers derived from primary lung adenocarcinoma microarrays.

Sample Metadata Fields

Sex, Age, Specimen part, Disease, Disease stage

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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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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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