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rna seq datasets  (Philips Healthcare)

 
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    Philips Healthcare rna seq datasets
    Rna Seq Datasets, supplied by Philips Healthcare, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/rna+seq+datasets/datasets+rna+seq/pm42169409-78-32-45
    Average 86 stars, based on 1 article reviews
    rna seq datasets - by Bioz Stars, 2026-10
    86/100 stars

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    Related Articles

    RNA Sequencing:

    Article Title: The circular RNA circP5CS1 coordinates plant immunity by sequestering miR167 to modulate ARF6/8 signaling and repressing P5CS1-mediated proline biosynthesis in Arabidopsis.
    Article Snippet: .. 207 208 Reciprocal regulation between circP5CS1 and P5CS1 transcript levels in 209 Arabidopsis 210 To investigate the potential regulatory relationship between circP5CS1 and 211 its host gene P5CS1, we reanalyzed publicly available RNA-seq datasets from 212 17 Arabidopsis mutants impaired in RNA processing or splicing (Philips et al., 213 Jo urn al Pr e-p roo f 9 2020). ..



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    Image Search Results


    Single-cell transcriptomic analysis of liver fibrosis. (A) Quality control metrics before cell filtering, including the distribution of gene counts (nFeature_RNA), UMI counts (nCount_RNA), and the percentages of mitochondrial and hemoglobin genes across samples. (B) Cell clustering of liver fibrosis samples. (C) Cell-type annotation of single-cell RNA-seq data. (D) Cell cycle analysis of single-cell transcriptomic data. (E) Proportional changes of different cell types between normal and fibrotic groups. (F) Expression distribution of Acot9, Aldh1b1, and Pck2 across different cell types.

    Journal: Frontiers in Immunology

    Article Title: Identification of mitochondria-related biomarkers in liver fibrosis via interpretable machine learning and WGCNA: transcriptomic analysis and In Vivo validation

    doi: 10.3389/fimmu.2026.1705706

    Figure Lengend Snippet: Single-cell transcriptomic analysis of liver fibrosis. (A) Quality control metrics before cell filtering, including the distribution of gene counts (nFeature_RNA), UMI counts (nCount_RNA), and the percentages of mitochondrial and hemoglobin genes across samples. (B) Cell clustering of liver fibrosis samples. (C) Cell-type annotation of single-cell RNA-seq data. (D) Cell cycle analysis of single-cell transcriptomic data. (E) Proportional changes of different cell types between normal and fibrotic groups. (F) Expression distribution of Acot9, Aldh1b1, and Pck2 across different cell types.

    Article Snippet: Single-cell RNA sequencing (scRNA-seq) datasets were obtained from GSE145086 and GSE233084 , both generated using the 10X Genomics platform ( , ).

    Techniques: Single Cell, Control, RNA Sequencing, Cell Cycle Assay, Expressing