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accession-icon SRP026334
Global small RNA analysis in fast-growing Arabidposis thaliana with elevated level of ATP and sugars
  • organism-icon Arabidopsis thaliana
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

The sRNA profiles of the leaf and the root of 20-day-old plants were sequenced and the impacts of high energy status on sRNA expression were analyzed Overall design: 8 samples consisting of wild type, overexpressed line 7 and 21, and AtPAP2-mutant.

Publication Title

Global small RNA analysis in fast-growing Arabidopsis thaliana with elevated concentrations of ATP and sugars.

Alternate Accession IDs

GSE48309

Sample Metadata Fields

Subject

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accession-icon GSE18534
Mouse small cell lung cancer model
  • organism-icon Mus musculus
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

A mouse model for human small cell lung carcinoma (SCLC) has been developed based on evidence in human tumors that the tumor suppressor functions of RB and p53 are defective in more than 90% of SCLC cases. We also developed another mouse model also combines loss of p130 (Rbl2), an RB-related gene, with deletion of RB and p53. These two mouse tumors were shown to closely resemble human SCLC.

Publication Title

Loss of p130 accelerates tumor development in a mouse model for human small-cell lung carcinoma.

Alternate Accession IDs

E-GEOD-18534

Sample Metadata Fields

Specimen part

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accession-icon SRP071643
SC3-consensus clustering of single cell RNA-Seq data
  • organism-icon Homo sapiens
  • sample-icon 384 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

We report a new unsupervised clustering tool for single cell RNA-seq data called SC3. We show that biologically relevant information can be obtained from preneoplastic cells of patients with myeloprolifertive disease. Overall design: examination of three different patients with myeloproloferative disease

Publication Title

SC3: consensus clustering of single-cell RNA-seq data.

Alternate Accession IDs

GSE79102

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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