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accession-icon GSE21572
Expression data from human stomach cell lines (MKN45 and MKN45P)
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)

Description

Analysis to find splicing variants that are differentially expressed in a highly metastatic stomach cancer cell line, MKN45P, versus its parental cell line, MKN45

Publication Title

Identification of a novel protein isoform derived from cancer-related splicing variants using combined analysis of transcriptome and proteome.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon DRP004758
Fine selection of up-regulated genes duirng ovulation by in vivo induction of oocyte maturation and ovulation in zebrafish
  • organism-icon Danio rerio
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Two essential processes, oocyte maturation and ovulation, before oocytes become fertilizable that are independently induced but co-operatively proceeded at the final step in oogenesis. Eventhough these two processes are induced by same maturation-inducing steroid, 17, 20 beta-dihydroxy-4-pregnen-3-one (17, 20 beta-DHP), in teleost, the receptor for each pathway is suggested to be different and thus signal transduction pathways are different. While much progresses achieved on the molecular mechanisms for induction of oocyte maturation, the mechanisms to induce ovulation is under elucidation. Previously we established the procedure that can make it possible to prepare the ovarian tissue which contains oocyte maturation-induced oocytes in vivo. In the same way, ovulation can be induced in alive zebrafish. Thus it became possible to select the genes up-regulated according to ovulation by compare the gene expression between maturation-inducing genes in matured oocytes and both maturation and ovulation-inducing genes in ovulated eggs. In vivo bioassay has been applied to prepare maturated and ovulated ovarian samples. Specifically up-regulated genes to induce ovulation will be selected by RNA-seq analysis. The mRNA abundance of highly up-regulated genes will be confirmed by q-PCR analysis. By this project, ovulation-inducing genes will be selected and its roles in induction of ovulation will be addressed in the future.

Publication Title

No associated publication

Sample Metadata Fields

No sample metadata fields

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accession-icon DRP004756
Identification of ovulation-inducing genes selected by the method for in vivo induction of oocyte maturation and ovulation in zebrafish
  • organism-icon Danio rerio
  • sample-icon 10 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

To identify ovulation-inducing genes, RNAseq analysis was carried out using samples prepared by in vivo assay system in zebrafish.

Publication Title

No associated publication

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE24580
Diosgenin supplementation effect on liver
  • organism-icon Mus musculus
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Expression profile of liver of ICR mice (13-week old) treated with control diet (CRF-1) or CRF-1 containing 500 ppm diosgenin for 4 weeks.

Publication Title

No associated publication

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE31210
Gene expression data for pathological stage I-II lung adenocarcinomas
  • organism-icon Homo sapiens
  • sample-icon 230 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Identification of genes up-regulated in ALK-positive and EGFR/KRAS/ALK-negative lung adenocarcinomas.

Publication Title

Identification of genes upregulated in ALK-positive and EGFR/KRAS/ALK-negative lung adenocarcinomas.

Sample Metadata Fields

Sex, Age, Specimen part

View Samples
accession-icon GSE35784
Gene expression profile of pediatric AML
  • organism-icon Homo sapiens
  • sample-icon 130 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Gene expression data were obtained from 130 pediatric AML patients who were enrolled on the AML99 study conducted by the Japanese Childhood AML Cooperative Study Group.

Publication Title

No associated publication

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE7553
Gene Expression Patterns Involved in the Malignant Transformation and Progression of Metastatic Melanoma
  • organism-icon Homo sapiens
  • sample-icon 86 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Metastatic melanoma is a deadly disease while non-metastatic melanoma and other cutaneous tumor types are usually cured with surgical removal of the primary tumors. This study evaluated gene expresion to determine if gene expression differences existed which would allow one to identify the metastatic tumors based on the expression of specific genes.

Publication Title

The gene expression profiles of primary and metastatic melanoma yields a transition point of tumor progression and metastasis.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE20196
Gene expression profile of poorly differentiated synovial sarcoma
  • organism-icon Homo sapiens
  • sample-icon 34 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Poorly differentiated type synovial sarcoma (PDSS) is a variant of synovial sarcoma characterized by predominantly round or short-spindled cells. Although accumulating evidence from clinicopathological studies suggests a strong association between this variant of synovial sarcoma and poor prognosis, little has been reported on the molecular basis of PDSS. To gain insight into the mechanism(s) that underlie the emergence of PDSS, we analyzed the gene expression profiles of 34 synovial sarcoma clinical samples, including 5 cases of PDSS, using an oligonucleotide microarray. In an unsupervised analysis, the 34 samples fell into 3 groups that correlated highly with histological subtype, namely, monophasic, biphasic, and poorly differentiated types. PDSS was characterized by down-regulation of genes associated with neuronal and skeletal development and cell adhesion, and up-regulation of genes on a specific chromosomal locus, 8q21.11. This locus-specific transcriptional activation in PDSS was confirmed by reverse transcriptase (RT)-PCR analysis of 9 additional synovial sarcoma samples. Our results indicate that PDSS tumors constitute a distinct genetic group based on expression profiles.

Publication Title

Gene expression profiling of synovial sarcoma: distinct signature of poorly differentiated type.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE14827
Gene expression profiles from osteosarcpma samples
  • organism-icon Homo sapiens
  • sample-icon 26 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Osteosarcoma patients with development of pulmonary metastasis have still poorer prognosis in spite of aggressive treatment. However, molecular mechanism of metastasis is still unknown.

Publication Title

Reduced argininosuccinate synthetase is a predictive biomarker for the development of pulmonary metastasis in patients with osteosarcoma.

Sample Metadata Fields

Sex, Age

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accession-icon GSE28284
Effects of genome architecture and epigenetic factors on susceptibility of promoter CpG islands to aberrant DNA methylation induction.
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Aberrant DNA methylation is induced at specific promoter CpG islands (CGIs) in contrast with mutations. The specificity is influenced by genome architecture and epigenetic factors, but their relationship is still unknown. In this study, we isolated promoter CGIs susceptible and resistant to aberrant methylation induction during prostate and breast carcinogenesis. The effect of genome architecture was more evident for promoter CGIs susceptible in both of the two tissues than for promoter CGIs susceptible only in one tissue. Multivariate analysis of promoter CGIs with tissue-nonspecific susceptibility showed that genome architecture, namely a remote location from SINE (OR=5.98; 95% CI=2.33-15.34) and from LINE (OR=2.08; 95% CI=1.03-4.21), was associated with increased susceptibility, independent of epigenetic factors such as the presence of RNA polymerase II (OR=0.09; 95% CI=0.02-0.48) and H3K27me3 (OR=3.28; 95% CI=1.17-9.21). These results showed that methylation susceptibility of promoter CGIs is determined both by genome architecture and epigenetic factors, independently.

Publication Title

Effects of genome architecture and epigenetic factors on susceptibility of promoter CpG islands to aberrant DNA methylation induction.

Sample Metadata Fields

Cell line

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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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