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transcriptome sequencing data  (Novogene)

 
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    Novogene transcriptome sequencing data
    Transcriptome Sequencing Data, supplied by Novogene, 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/transcriptomic+sequencing+data/sequencing+transcriptome/pmc13000926-91-10-5
    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: An astragalus polysaccharide-loaded hydrogel dressing enhances diabetic wound healing via dual-mode electrical stimulation
    Article Snippet: .. The transcriptomic sequencing was performed by the platform of Novogene Co., Ltd, including library construction, high-throughput sequencing, and subsequent analysis (i.e., Differential gene expression analysis, Gene Ontology enrichment analysis, and Gene Set Enrichment Analysis). ..

    Article Title: A Substrate-Dependent Bifunctional Dioxygenase from Fraxinus chinensis for O -Demethylation and C8-Hydroxylation of Coumarins.
    Article Snippet: .. Transcriptome sequencing and bioinformatic analyses were performed by Novogene Co., Ltd. (Beijing, China). .. Restriction enzymes NdeI and HindIII were obtained from New England Biolabs (Ipswich, MA, USA).

    Article Title: Integrative whole-transcriptome analysis of circRNAs, lncRNAs, miRNAs, and mRNAs reveals regulatory networks in mouse brain during Toxoplasma gondii infection.
    Article Snippet: .. We thank Novogene Co., Ltd., China. for technical assistance in Whole transcriptome sequencing. ..

    Article Title: Genome-wide characterisation of the myosin light chain gene family in Chinese perch (Siniperca chuatsi) and its expression patterns in muscle fibre types and injury response.
    Article Snippet: The Class II myosin light chain (myl) genes in Chinese perch (Siniperca chuatsi) have not yet been systematically characterised, and relationships with muscle fibre specification, development, and injury-associated remodelling remain unclear.. In this study, fast and slow muscle fibres were initially distinguished using myofibrillar ATPase histochemistry.. Subsequently, genome-wide mining identified 16 Class II myl genes, comprising eight essential and eight regulatory light-chain subunits.

    Article Title: Designer Dynamic DNA Nanoaggregate in Living Cell for Mitochondrial Energy Restriction.
    Article Snippet: .. The qualified RNA samples were then sent to Novogene Biotech Co., Ltd. (Beijing, China) for transcriptome sequencing. ..

    Next-Generation Sequencing:

    Article Title: An astragalus polysaccharide-loaded hydrogel dressing enhances diabetic wound healing via dual-mode electrical stimulation
    Article Snippet: .. The transcriptomic sequencing was performed by the platform of Novogene Co., Ltd, including library construction, high-throughput sequencing, and subsequent analysis (i.e., Differential gene expression analysis, Gene Ontology enrichment analysis, and Gene Set Enrichment Analysis). ..

    Gene Expression:

    Article Title: An astragalus polysaccharide-loaded hydrogel dressing enhances diabetic wound healing via dual-mode electrical stimulation
    Article Snippet: .. The transcriptomic sequencing was performed by the platform of Novogene Co., Ltd, including library construction, high-throughput sequencing, and subsequent analysis (i.e., Differential gene expression analysis, Gene Ontology enrichment analysis, and Gene Set Enrichment Analysis). ..



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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