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Canada-0-SCALES ไดเรกทอรีที่ บริษัท
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ข่าว บริษัท :
- GEO Accession viewer
Here, we obtained single-cell transcriptomes of mouse kidney tissue from whole organs and from defined kidney zones (cortex, outer and inner medulla) and applied computational methods to reconstruct the spatial position of kidney tubule cells along the corticomedullary axis based on their transcriptomes
- GSE145688 - Kidney single-cell transcriptomes predict spatial . . .
ABSTRACT: Single-cell transcriptomics from dissociated organs lack information regarding the spatial origin of each cell, which limits their interpretation, particularly in complex and regionally heterogeneous tissues This is relevant in the kidney, where cell types are exposed to a wide spectrum of cellular microenvironments along the corticomedullary axis, including steep gradients of
- GEO Accession viewer
GSE145688 Kidney single-cell transcriptomes predict spatial corticomedullary gene expression and tissue osmolality gradients [Drop-seq] GSE145690 Kidney single-cell transcriptomes predict spatial corticomedullary gene expression and tissue osmolality gradients Relations BioSample SAMN14161530 SRA SRX7775600 Supplementary file Size Download File
- GEO Browser - GEO - NCBI
Mus musculus 15 XLSX SRA Run Selector Christian Hinze Nov 26, 2020 GSE145688 Kidney single-cell transcriptomes predict spatial corticomedullary gene expression and tissue osmolality gradients [Drop-seq] Expression profiling by high throughput sequencing Mus musculus 5 TXT SRA Run Selector Christian Hinze Nov 26, 2020 GSE145689
- NCAPG upregulation mediated by four microRNAs combined with activation . . .
In the present study, the gene expression levels and the correlations between two genes were assessed using the UALCAN database
- GEO Browser - GEO - NCBI
Gene Expression Omnibus (GEO) is a database repository of high throughput gene expression data and hybridization arrays, chips, microarrays
- Enhanced Directed Random Walk for the Identification of Breast Cancer . . .
Therefore, an enhanced DRW (eDRW+) is proposed to identify breast cancer prognostic markers from multiclass expression data An improved weight strategy using one-way ANOVA (F-test) and pathway selection based on the greatest reproducibility power is proposed in eDRW+
- Germ cells and mammary gland transcritome comparison generate a . . .
We aimed to identify breast cancer genetic signatures in order to predict survival Methods: An in silico analysis using publicly available breast cancer datasets (GSE27715, GSE54126, GSE1456 and TCGA) was carried out
- Transcriptional diversity and bioenergetic shift in human . . . - Nature
Here, we establish a robust method for the identification of global transcriptomic changes in rare metastatic cells during seeding using single-cell RNA sequencing and patient-derived-xenograft
- The Origins of Breast Cancer Prognostic Gene Expression Profiles
To investigate if these gene expression signatures were of somatic or germline origin and to assess the contribution of different cell types to the induction of these signatures, we have performed a series of expression profiling experiments in a mouse model of metastatic breast cancer
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