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accession-icon SRP013931
Initial analysis of transcript levels in zebrafish with advancing age
  • organism-icon Danio rerio
  • sample-icon 20 Downloadable Samples
  • Technology Badge IconIlluminaGenomeAnalyzerIIx

Description

This project aims at an initial characterization of changes in gene expression in zebrafish with advancing age. Transcript levels are determined in several tissues of zebrafish with differing ages using RNA-seq. Differentially expressed genes are determined to pinpoint genes that are differently regulated in young and old zebrafish. Results will be compared with other species to identify common pathways of ageing.

Publication Title

No associated publication

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP039085
Homo sapiens strain:HL-60 Transcriptome or Gene expression
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIlluminaGenomeAnalyzerIIx

Description

Transcriptome of human HL-60 and HEK-293 cells depending on culture cell density

Publication Title

No associated publication

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon E-MEXP-1006
Transcription profiling time series of finite life span and immortal non-malignant human mammary epithelial cell lines
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

We analyzed gene expression in 184 (finite life span) and HMT3522 S1 (immortal non-malignant) HMECs on successive days (3, 5, and 7) post-seeding in a laminin-rich extracellular matrix assay. Both HMECs underwent growth arrest in G0/G1 and differentiated into polarized acini between days 5 and 7.

Publication Title

Gene expression signature in organized and growth-arrested mammary acini predicts good outcome in breast cancer.

Sample Metadata Fields

Sex, Specimen part, Cell line, Time

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accession-icon DRP001187
Simultaneous RNA-seq of bone marrow derived dendritic cells from Mus Musculus strain C57BL6/J activated with lipopolysaccharide over a period of 24 hours.
  • organism-icon Mus musculus
  • sample-icon 29 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer IIx

Description

The innate immune response is primarily mediated by the Toll-like receptors functioning through the Myd88-dependent and TRIF-dependent pathways. Despite being widely studied, it is not yet completely understood and systems-level analyses have been lacking. In this study, we identified a high-probability network of genes activated during the innate immune response using a novel approach to analyze time course gene expression profiles of activated immune cells in combination with a large gene regulatory and protein-protein interaction network. We classified the immune response into three consecutive time-dependent stages and identified the most probable paths between genes showing a significant change in expression at each stage. The resultant network contained several novel and known regulators of the innate immune response, many of which did not show any observable change in expression at the sampled time points. The response network shows the dominance of genes from specific functional classes during different stages of the immune response. It also suggests a role for the protein phosphatase 2a catalytic subunit a in the regulation of the immunoproteasome during the late phase of the response. In order to clarify the differences between the Myd88-dependent and TRIF-dependent pathways in the innate immune response, time course gene expression profiles from Myd88-knockout and TRIF-knockout dendritic cells were analyzed. Their response networks suggest the dominance of the MyD88 dependent pathway in the innate immune response, and an association of the circadian regulators and immunoproteasomal degradation with the TRIF-dependent pathway. The response network presented here provides the most probable associations between genes expressed in the early and the late phases of the immune response, while taking into account the intermediate regulators. We propose that the method described here can also be used in the identification of time-dependent gene subnetworks in other biological systems.

Publication Title

Discovery of Intermediary Genes between Pathways Using Sparse Regression.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE44029
Expression data from SW480 cells with Gankyrin knockdown
  • organism-icon Homo sapiens
  • sample-icon 5 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

we performed genome-wide screening using SW480 cells with Gankyrin knockdown on an Affymetrix gene expression array to identify the transcriptional targets of Gankyrin

Publication Title

Gankyrin activates IL-8 to promote hepatic metastasis of colorectal cancer.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon SRP151477
Deciphering the C. elegans embryonic transcriptome with tissue, time, and alternative splicing resolution
  • organism-icon Caenorhabditis elegans
  • sample-icon 82 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

We have used FACS to isolate fluorescent cells at multiple time points from synchronized embryos containing early and highly specific tissue/lineage markers. We then carried out RNA-seq, and observe dramatic differences in gene expression levels both between cell-types, and over time within the same population. Furthermore, we observe differential transcript usage between cell-types and over time, including differential promoter and differential exon usage that leads to additional differences between cell types.

Publication Title

No associated publication

Sample Metadata Fields

Sex, Age, Specimen part, Disease

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accession-icon SRP000931
Melanoma Cell Transcriptome
  • organism-icon Homo sapiens
  • sample-icon 14 Downloadable Samples
  • Technology Badge IconIlluminaGenomeAnalyzerII

Description

Paired end sequencing of cDNA isolated from individual melanoma samples via the Illumina sequencing platform to identify genetic aberrations that may play a role in melanoma genesis.

Publication Title

Integrative analysis of the melanoma transcriptome.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP011371
Escherichia coli str. K-12 substr. MG1655 Transcriptome or Gene expression
  • organism-icon Escherichia coli
  • sample-icon 9 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer II

Description

The goal was to establish a robust and scalable RNA-seq process applicable to cultured bacteria as well as to complex community transcriptomes. To this end, we evaluated rRNA depletion methods and chose a protocol that eliminates rRNA reads efficiently and robustly, and largely irrespective of the quality of the RNA input sample.

Publication Title

No associated publication

Sample Metadata Fields

Specimen part, Cell line

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accession-icon SRP052182
Arthropod Cell Line RNA Seq
  • organism-icon Anopheles gambiae
  • sample-icon 7 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Transcriptome sequencing of arthropod cell lines

Publication Title

No associated publication

Sample Metadata Fields

Specimen part, Disease, Cell line

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accession-icon SRP052081
Arthropod Cell Line RNA Seq
  • organism-icon Anopheles gambiae
  • sample-icon 7 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Transcriptome sequencing of arthropod cell lines

Publication Title

No associated publication

Sample Metadata Fields

Specimen part, Disease, Cell line

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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