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transcriptome sequencing data  (Mendeley Ltd)

 
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    Mendeley Ltd transcriptome sequencing data
    Transcriptome Sequencing Data, supplied by Mendeley Ltd, 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/transcriptome+sequencing+data/data+sequencing/pm41801219-580-1-11
    Average 86 stars, based on 1 article reviews
    transcriptome sequencing data - by Bioz Stars, 2026-09
    86/100 stars

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    Related Articles

    Sequencing:

    Article Title: Protocol for enhancing CRISPR-Cas9 genome editing using histone deacetylase inhibition and engineered virus-like particle delivery
    Article Snippet: .. Raw Sanger Sequencing data , Mendeley , https://doi.org/10.17632/33tm3dd9dw.1. .. Raw immunofluorescent microscopy data , Mendeley , https://doi.org/10.17632/33tm3dd9dw.1.

    Article Title: A thioacrylamide-based compound directly counteracts hepatic fibrosis with profound anti-obesity action
    Article Snippet: .. The sequencing data supporting this study are openly available at Mendeley Data (doi 10.17632/49t2nkg73c.1). ..

    Article Title: Whole-genome sequence dataset of Pasteurella multocida strain EH32 isolated from buffaloes in Vietnam
    Article Snippet: .. The raw sequencing data are publicly in Mendeley data (DOI:10.17632/nyczcvbygc.1), and the draft genome assembly has been deposited in DDBJ/GenBank/EMBL (accession: JBRUXC000000000 ). ..

    RNA Sequencing:


    Article Title: Tescalcin is a phagocytic checkpoint driving immune escape and limiting immunotherapeutic efficacy in hepatocellular carcinoma.
    Article Snippet: .. These associations were independently 121 validated using single-cell RNA sequencing data (Mendeley Data: skrx2fz79n), which 122 confirmed a correlation between high TESC expression and diminished efficacy of αPD-1 123 therapy (Figure 1G). ..

    Article Title: Dynamin 2 Regulates Mitochondrial Mitotic Fission in Pulmonary Hypertension
    Article Snippet: .. Processed RNA-seq data are publicly available via Mendeley data (10.17632/m8s629jyg3.1). ..

    Article Title: The inhibitory effect of hepatic cancer energy metabolism on immune checkpoint therapy: perspectives from single-cell multi-omics analysis
    Article Snippet: .. Integrated single-cell RNA-seq data (GEO, Mendeley) were analyzed using Seurat, AUCell, pySCENIC, CellChat, and Monocle. ..

    Single Cell:

    Article Title: Tescalcin is a phagocytic checkpoint driving immune escape and limiting immunotherapeutic efficacy in hepatocellular carcinoma.
    Article Snippet: .. These associations were independently 121 validated using single-cell RNA sequencing data (Mendeley Data: skrx2fz79n), which 122 confirmed a correlation between high TESC expression and diminished efficacy of αPD-1 123 therapy (Figure 1G). ..

    Article Title: The inhibitory effect of hepatic cancer energy metabolism on immune checkpoint therapy: perspectives from single-cell multi-omics analysis
    Article Snippet: .. Integrated single-cell RNA-seq data (GEO, Mendeley) were analyzed using Seurat, AUCell, pySCENIC, CellChat, and Monocle. ..

    Expressing:

    Article Title: Tescalcin is a phagocytic checkpoint driving immune escape and limiting immunotherapeutic efficacy in hepatocellular carcinoma.
    Article Snippet: .. These associations were independently 121 validated using single-cell RNA sequencing data (Mendeley Data: skrx2fz79n), which 122 confirmed a correlation between high TESC expression and diminished efficacy of αPD-1 123 therapy (Figure 1G). ..



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    Identification of core genes associated with macrophage immune training and heart failure. (A) Schematic overview of human-derived macrophage trained immunity model and <t>transcriptomic</t> profiling workflow ( GSE235897 ). (B) The volcano plot and (C) DEGs heatmap of hMDMs from trained (n=3) and untrained (n=3) samples in the macrophage-trained immunity dataset GSE235897 (|log2FC| ≥ 0.585, p < 0.05). (D) Sample clustering dendrogram of GSE135055 dataset based on gene expression profiles. (E) Scale-free topology fit index and (F) mean connectivity analysis across a range of soft-thresholding powers. (G) Cluster dendrogram of genes showing co-expression modules identified by WGCNA in database GSE135055 . (H) Module-trait heatmap values represent correlation coefficients between healthy controls and HF samples (* p < 0.05, ** p < 0.01). (I) Venn diagram showing the overlap among heart failure DEGs, trained-immunity DEGs, and WGCNA module genes.
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    Image Search Results


    Identification of core genes associated with macrophage immune training and heart failure. (A) Schematic overview of human-derived macrophage trained immunity model and transcriptomic profiling workflow ( GSE235897 ). (B) The volcano plot and (C) DEGs heatmap of hMDMs from trained (n=3) and untrained (n=3) samples in the macrophage-trained immunity dataset GSE235897 (|log2FC| ≥ 0.585, p < 0.05). (D) Sample clustering dendrogram of GSE135055 dataset based on gene expression profiles. (E) Scale-free topology fit index and (F) mean connectivity analysis across a range of soft-thresholding powers. (G) Cluster dendrogram of genes showing co-expression modules identified by WGCNA in database GSE135055 . (H) Module-trait heatmap values represent correlation coefficients between healthy controls and HF samples (* p < 0.05, ** p < 0.01). (I) Venn diagram showing the overlap among heart failure DEGs, trained-immunity DEGs, and WGCNA module genes.

    Journal: Frontiers in Immunology

    Article Title: Identification of MTURN as a trained immunity-related biomarker for heart failure via integrative transcriptomic machine learning analysis and experimental validation

    doi: 10.3389/fimmu.2026.1739660

    Figure Lengend Snippet: Identification of core genes associated with macrophage immune training and heart failure. (A) Schematic overview of human-derived macrophage trained immunity model and transcriptomic profiling workflow ( GSE235897 ). (B) The volcano plot and (C) DEGs heatmap of hMDMs from trained (n=3) and untrained (n=3) samples in the macrophage-trained immunity dataset GSE235897 (|log2FC| ≥ 0.585, p < 0.05). (D) Sample clustering dendrogram of GSE135055 dataset based on gene expression profiles. (E) Scale-free topology fit index and (F) mean connectivity analysis across a range of soft-thresholding powers. (G) Cluster dendrogram of genes showing co-expression modules identified by WGCNA in database GSE135055 . (H) Module-trait heatmap values represent correlation coefficients between healthy controls and HF samples (* p < 0.05, ** p < 0.01). (I) Venn diagram showing the overlap among heart failure DEGs, trained-immunity DEGs, and WGCNA module genes.

    Article Snippet: For single-cell transcriptomic data, we accessed the SCP1303 project from the Broad Institute ( https://singlecell.broadinstitute.org/single_cell ), which includes raw scRNA-seq data from failing human hearts with dilated and hypertrophic cardiomyopathy.

    Techniques: Derivative Assay, Gene Expression, Expressing

    Five heart failure transcriptomic datasets were integrated with a macrophage-trained immunity model to identify immune-related biomarkers. Through DEGs analysis, WGCNA, CIBERSORT, and six machine learning algorithms, hub genes were prioritized with MTURN emerging as the top candidate. Its potential was further validated by scRNA-seq analysis, which confirmed MTURN enrichment in cardiac macrophages. Finally, MTURN expression was validated using previously published heart failure transcriptomic data and in vitro experiments.

    Journal: Frontiers in Immunology

    Article Title: Identification of MTURN as a trained immunity-related biomarker for heart failure via integrative transcriptomic machine learning analysis and experimental validation

    doi: 10.3389/fimmu.2026.1739660

    Figure Lengend Snippet: Five heart failure transcriptomic datasets were integrated with a macrophage-trained immunity model to identify immune-related biomarkers. Through DEGs analysis, WGCNA, CIBERSORT, and six machine learning algorithms, hub genes were prioritized with MTURN emerging as the top candidate. Its potential was further validated by scRNA-seq analysis, which confirmed MTURN enrichment in cardiac macrophages. Finally, MTURN expression was validated using previously published heart failure transcriptomic data and in vitro experiments.

    Article Snippet: For single-cell transcriptomic data, we accessed the SCP1303 project from the Broad Institute ( https://singlecell.broadinstitute.org/single_cell ), which includes raw scRNA-seq data from failing human hearts with dilated and hypertrophic cardiomyopathy.

    Techniques: Expressing, In Vitro