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accession-icon GSE11114
Comparison of murine masticatory and limb skeletal muscle
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Expression 430A Array (moe430a)

Description

Distinctions between craniofacial and axial muscles exist from the onset of development and throughout adulthood. The masticatory muscles are a specialized group of craniofacial muscles that retain embryonic fiber properties throughout adulthood, suggesting that the developmental origin of these muscles may govern a pattern of expression that differs from limb muscles. To determine the extent of these differences, expression profiling of total RNA isolated from the masseter and tibialis anterior (TA) muscles of adult female mice was performed, which identified transcriptional changes in unanticipated functional classes of genes in addition to those associated with fiber type. In particular, the masseters displayed a reduction of transcripts associated with load-sensing and anabolic processes, and heightened expression of genes associated with stress. Consistent with these observations were a significantly smaller fiber cross-sectional area in masseters, significantly elevated load-sensing signaling (phosphorylated Focal Adhesion Kinase (FAK)), and increased apoptotic index in masseters compared to TA muscles. Based on these results, we hypothesize that masticatory muscles may sense and respond to load differently than limb muscles, where the drive for anabolic processes is reduced, and cell stress mediated processes are enhanced. These results establish a novel classification for the masseter muscle in the spectrum of skeletal muscle allotypes, and may provide insight into the molecular basis for specific muscle-related pathologies associated with masticatory muscles.

Publication Title

Expression profiling reveals heightened apoptosis and supports fiber size economy in the murine muscles of mastication.

Sample Metadata Fields

No sample metadata fields

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accession-icon E-MEXP-1288
Transcription profiling of mouse masseter and tibialis anterior muscles to determine expression differences between muscle groups
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Expression 430A Array (moe430a)

Description

Masseter and Tibialis anterior muscles from adult female control mice to determine expression differences between muscle groups

Publication Title

Expression profiling reveals heightened apoptosis and supports fiber size economy in the murine muscles of mastication.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE8512
Expression data from mouse bone marrow macrophages from a strain intercross
  • organism-icon Mus musculus
  • sample-icon 207 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Bone marrow macrophages were cultured from 16 week old apoE-deficient F2 mice from an AKRxDBA/2 intercross

Publication Title

Sex specific gene regulation and expression QTLs in mouse macrophages from a strain intercross.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE16987
A new gene expression signature, the ClinicoMolecular Triad Classification, may improve prediction and prognostication of breast cancer at the time of diagnosis
  • organism-icon Homo sapiens
  • sample-icon 161 Downloadable Samples
  • Technology Badge IconIllumina humanRef-8 v2.0 expression beadchip

Description

When making treatment decisions, oncologists often stratify breast cancers into a low-risk group (ER+, low grade); an intermediate-risk group (ER+, high grade); and a high-risk group that includes Her2+ and triple-negative (ER-/PR-/Her2-) tumors. None of the currently available gene signatures correlates to this clinical classification. We aimed to develop a test that is practical for the oncologists, that offers both molecular characterization of BCs, and improved prediction of prognosis and treatment response. We investigated the molecular basis of such clinical practice by grouping Her2+ and triple-negative breast cancers together during clustering analyses on the genome-wide gene expression profiles of our training cohort, mostly derived from fine needle aspiration biopsies (FNABs) of 149 consecutive evaluable Breast cancers. The analyses consistently divided these tumors into a three-cluster pattern, similar to clinical risk-stratification groups, that was reproducible in published microarray databases (n=2487) annotated with clinical outcomes. The clinicopathologic parameters of each of these three molecular groups were also similar to clinical classification. The low-risk group had good outcomes and benefited from endocrine therapy. Both intermediate- and high-risk groups had poor outcomes and were resistant to endocrine therapy. The latter demonstrated the highest rate of complete pathological response to neoadjuvant chemotherapy; the highest activities in MYC, E2F1, Ras, -Catenin and IFN- pathways; and poor prognosis predicted by 14 independent prognostic signatures. Based on a multivariate analysis, this new gene signature, termed ClinicoMolecular Triad Classification, predicted recurrence and treatment response better than all pathologic parameters and other prognostic signatures.

Publication Title

A new gene expression signature, the ClinicoMolecular Triad Classification, may improve prediction and prognostication of breast cancer at the time of diagnosis.

Sample Metadata Fields

Specimen part

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accession-icon GSE16984
Comparability and concordance of replicated microarray data.
  • organism-icon Homo sapiens
  • sample-icon 30 Downloadable Samples
  • Technology Badge IconIllumina humanRef-8 v2.0 expression beadchip

Description

To measures the comparability and concordance of Illumina microarray, a series of 30 samples of Universal Human Reference RNA (UHRR) were set as controls for every single chip of total 30 Human-Ref V2 BeadChips. The average bead number of the 30 arrays was 42.38.1 for any bead type over the 22,184 probes. A high average correlation coefficient (r) value was obtained as 0.99080077 relative to each other of the expression intensity values from the 30 duplicate UHRR samples.

Publication Title

A new gene expression signature, the ClinicoMolecular Triad Classification, may improve prediction and prognostication of breast cancer at the time of diagnosis.

Sample Metadata Fields

Disease

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accession-icon GSE19345
Human Cytomegalovirus Infection Causes Premature and Abnormal Differentiation of Human Neural Progenitor Cells
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Our results suggest that HCMV infection disrupts the self-renewal capacity of NPCs and influences their differentiation.

Publication Title

Human cytomegalovirus infection causes premature and abnormal differentiation of human neural progenitor cells.

Sample Metadata Fields

Specimen part

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accession-icon GSE118754
Transcriptome Expression Data from Resected Operative Ileal Mucosa Specimens in a cohort of patients with Crohns Disease
  • organism-icon Homo sapiens
  • sample-icon 64 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Transcriptome Array 2.0 (hta20)

Description

Affymetrix human whole transcriptome array (HTA 2.0) completed on patients with Crohn's disease undergoing their first ileocolic resection

Publication Title

Predicting Risk of Postoperative Disease Recurrence in Crohn's Disease: Patients With Indolent Crohn's Disease Have Distinct Whole Transcriptome Profiles at the Time of First Surgery.

Sample Metadata Fields

Specimen part

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accession-icon SRP163661
Differential expression of genes in fibroblasts and epithelial cells infected with dsDNA viruses
  • organism-icon Homo sapiens
  • sample-icon 40 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

We studied changes in a whole transcriptome during dsDNA virus infection. Overall design: Fibroblasts (MRC5 & HFF) and epithelial cells (ARPE19) were infected with HCMV, HSV1 or Ad5 and total RNA was isolated at 48, 9, or 24 hpi, respectively. Total 15 treatments were used. There were 2 biological replicates analyzed per each treatment.

Publication Title

A tumor-specific endogenous repetitive element is induced by herpesviruses.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE60876
YAP and RUNX co-regulated genes in MCF10A
  • organism-icon Homo sapiens
  • sample-icon 30 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

An antagonistic interplay between YAP and RUNX where RUNX proteins abrogate YAP-mediated transcription of EMT and Stemness associated genes in mammary epithelial cells in an interaction dependent manner.

Publication Title

RUNX1 and RUNX3 protect against YAP-mediated EMT, stem-ness and shorter survival outcomes in breast cancer.

Sample Metadata Fields

Cell line

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accession-icon GSE134807
Etv1 controls the establishment of non-overlapping motor innervation of neighboring facial muscles during development
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The motor neurons innervating the muscles of facial expression are organized into somatotopic hindbrain clusters termed subnuclei. Each of the medial, intermediate, dorsolateral, and lateral subnuclei gives rise to a specific branch of the facial motor nerve (cranial nerve VII). How subnucleus-specific gene expression could mediate the accurate development of facial nerve projections was not well understood.

Publication Title

Etv1 Controls the Establishment of Non-overlapping Motor Innervation of Neighboring Facial Muscles during Development.

Sample Metadata Fields

Sex, Specimen part

View Samples
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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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