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-069978 arraystar human circrna microarray v1  (Agilent technologies)


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    Agilent technologies -069978 arraystar human circrna microarray v1
    069978 Arraystar Human Circrna Microarray V1, supplied by Agilent technologies, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/-069978+arraystar+human+circrna+microarray+v1/pmc10700118-123-6-7
    Average 90 stars, based on 1 article reviews
    -069978 arraystar human circrna microarray v1 - by Bioz Stars, 2026-09
    90/100 stars

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    Related Articles

    Microarray:

    Article Title: Prediction of a Potential Mechanism of Intervertebral Disc Degeneration Based on a Novel Competitive Endogenous RNA Network
    Article Snippet: GSE56081 , lncRNA , 10 , Degenerative nucleus pulposus , Nondegenerative nucleus pulposus , GPL15314 Arraystar Human LncRNA microarray V2.0 (Agilent_033010 Probe Name version). .. GSE67566 , circRNA , 10 , Degenerative nucleus pulposus , Nondegenerative nucleus pulposus , GPL19978 Agilent-069978 Arraystar Human CircRNA microarray V1. ..

    Article Title: Reveal the potential molecular mechanism of circRNA regulating immune-related mRNA through sponge miRNA in the occurrence and immune regulation of papillary thyroid cancer
    Article Snippet: GSE113629 , Xia Fada , GPL24741 Agilent-070156 Human_miRNA_V21.0_Microarray 046064 (gene name version) , 5 : 5 , 2019 , Tissue , miRNA. .. GSE93522 , Nianchun Peng , GPL19978 Agilent-069978 Arraystar Human CircRNA microarray V1 , 6 : 6 , 2017 , Tissue , circRNA. .. GSE173299 , Yushuang Sun , GPL21825 074301 Arraystar Human CircRNA microarray V2 , 3 : 3 , 2021 , Tissue , circRNA.

    Article Title: Comprehensive Analysis of circRNA-miRNA-mRNA Network in Cervical Squamous Cell Carcinoma by Integrated Analysis
    Article Snippet: .. GSE102686 , Jiao J , GPL19978 Agilent-069978 Arraystar Human CircRNA microarray V1 , 5: 5 , 2017. ..

    Article Title: circARL15 Plays a Critical Role in Intervertebral Disc Degeneration by Modulating miR-431-5p/DISC1
    Article Snippet: .. The GSE67567 dataset was acquired from the National Center of Biotechnology Information (NCBI) Gene Expression Omnibus database , on the basis of GPL15314 Arraystar Human LncRNA and mRNA microarray V2.0 (Agilent_033010 Probe Name version), GPL19449 Exiqon miRCURY LNA microRNA Array, 7th generation REV – hsa, mmu & rno (miRBase v18.0), and GPL19978 Agilent-069978 Arraystar Human CircRNA microarray V1. ..

    Article Title: Comprehensive analysis of potential ceRNA network and immune cell infiltration in intervertebral disc degeneration
    Article Snippet: .. GSE67566 , GPL19978 Agilent-069978 Arraystar Human CircRNA microarray V1 , 5 , 5. .. GSE63492 , GPL19449 Exiqon miRCURY LNA microRNA Array, seventh generation REV—hsa, mmu & rno (miRBase v18.0) , 5 , 5.

    Article Title: Identification of circRNA–miRNA–Immune-Related mRNA Regulatory Network in Gastric Cancer
    Article Snippet: circRNA , GSE83521 , Yan Zhang , GPL19978 Agilent-069978 Arraystar Human CircRNA microarray V1 , 6:6 , 2017 , Gastric tissue. .. GSE89143 , Junming Guo , GPL19978 Agilent-069978 Arraystar Human CircRNA microarray V1 , 3:3 , 2017 , Gastric tissue. .. miRNA , GSE93415 , Marek Sierżęga , GPL19071 Exiqon miRCURY LNA microRNA array; 7th generation REV - hsa, mmu, and rno; batch 208520-22; lot 35101-35101 (miRBase 19.0) , 20:20 , 2017 , Gastric tissue.

    Gene Expression:

    Article Title: circARL15 Plays a Critical Role in Intervertebral Disc Degeneration by Modulating miR-431-5p/DISC1
    Article Snippet: .. The GSE67567 dataset was acquired from the National Center of Biotechnology Information (NCBI) Gene Expression Omnibus database , on the basis of GPL15314 Arraystar Human LncRNA and mRNA microarray V2.0 (Agilent_033010 Probe Name version), GPL19449 Exiqon miRCURY LNA microRNA Array, 7th generation REV – hsa, mmu & rno (miRBase v18.0), and GPL19978 Agilent-069978 Arraystar Human CircRNA microarray V1. ..



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    <t>Microarray</t> transcriptomic signature of circRNAs in human papillary thyroid carcinoma. ( A ) Characteristics of six PTC patients were retrieved from the Gene Expression Omnibus database (GSE93522). PTC was compared with their paired contralateral normal thyroid tissues ( B ) Boxplots showing the distribution of the values of the selected samples. Median-centered values are indicated after log transform and quantile normalization. ( C ) Principal component analysis for data exploration. The geometrical projection for samples is based on the similarities and differences in the expression of 2895 circRNAs. Samples are plotted across two coordinates; axis 1 explained 52.1% of the variance, whereas axis 2 demonstrated 17% of the data variability. ( D ) Volcano plot displays statistical significance (−log10 p -value) versus magnitude of change (log2 fold change) in PTC compared with controls. Each dot represents a circRNA. The plot shows 137 significantly differentially expressed circRNAs (DEC): 115 upregulated (red dots) and 22 downregulated (blue dots). Analysis was performed using GEO2R software, with the p -value threshold at <0.05 and log fold changes (FC) at >1. ( E ) Heatmap for the 12 thyroid tissue specimens using the 137 differentially expressed circRNAs. There was an upregulation pattern of genes in patient samples. Clear differentiation of four PTC tissues and incomplete separation of two others are shown. ( F ) Principal component analysis to visualize how samples are related to each other. By using the deregulated genes, a complete demarcation was observed between PTC and normal tissues. Axes 1 and 2 explain 66.6% and 9.7% of the variability, respectively. ( G ) The top-up and downregulated circRNAs in PTC tissues. Derived protein-coding genes from which circRNAs were formed are shown. Fold change values are depicted at the end of the bars. ( H ) Frequency of tested circRNAs in the microarray according to their chromosomal localization. Y axis is log10 transformed, and the X axis represents the human chromosomes with removed missing chromosomes (chromosomes 18, 21, and Y). ( I ) Chromosomal ideograms represent the differentially expressed circRNAs annotated with lines in color at specific base-pair locations: blue for upregulated DECs and green for downregulated DECs.
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    <t>Microarray</t> transcriptomic signature of circRNAs in human papillary thyroid carcinoma. ( A ) Characteristics of six PTC patients were retrieved from the Gene Expression Omnibus database (GSE93522). PTC was compared with their paired contralateral normal thyroid tissues ( B ) Boxplots showing the distribution of the values of the selected samples. Median-centered values are indicated after log transform and quantile normalization. ( C ) Principal component analysis for data exploration. The geometrical projection for samples is based on the similarities and differences in the expression of 2895 circRNAs. Samples are plotted across two coordinates; axis 1 explained 52.1% of the variance, whereas axis 2 demonstrated 17% of the data variability. ( D ) Volcano plot displays statistical significance (−log10 p -value) versus magnitude of change (log2 fold change) in PTC compared with controls. Each dot represents a circRNA. The plot shows 137 significantly differentially expressed circRNAs (DEC): 115 upregulated (red dots) and 22 downregulated (blue dots). Analysis was performed using GEO2R software, with the p -value threshold at <0.05 and log fold changes (FC) at >1. ( E ) Heatmap for the 12 thyroid tissue specimens using the 137 differentially expressed circRNAs. There was an upregulation pattern of genes in patient samples. Clear differentiation of four PTC tissues and incomplete separation of two others are shown. ( F ) Principal component analysis to visualize how samples are related to each other. By using the deregulated genes, a complete demarcation was observed between PTC and normal tissues. Axes 1 and 2 explain 66.6% and 9.7% of the variability, respectively. ( G ) The top-up and downregulated circRNAs in PTC tissues. Derived protein-coding genes from which circRNAs were formed are shown. Fold change values are depicted at the end of the bars. ( H ) Frequency of tested circRNAs in the microarray according to their chromosomal localization. Y axis is log10 transformed, and the X axis represents the human chromosomes with removed missing chromosomes (chromosomes 18, 21, and Y). ( I ) Chromosomal ideograms represent the differentially expressed circRNAs annotated with lines in color at specific base-pair locations: blue for upregulated DECs and green for downregulated DECs.
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    <t>Microarray</t> transcriptomic signature of circRNAs in human papillary thyroid carcinoma. ( A ) Characteristics of six PTC patients were retrieved from the Gene Expression Omnibus database (GSE93522). PTC was compared with their paired contralateral normal thyroid tissues ( B ) Boxplots showing the distribution of the values of the selected samples. Median-centered values are indicated after log transform and quantile normalization. ( C ) Principal component analysis for data exploration. The geometrical projection for samples is based on the similarities and differences in the expression of 2895 circRNAs. Samples are plotted across two coordinates; axis 1 explained 52.1% of the variance, whereas axis 2 demonstrated 17% of the data variability. ( D ) Volcano plot displays statistical significance (−log10 p -value) versus magnitude of change (log2 fold change) in PTC compared with controls. Each dot represents a circRNA. The plot shows 137 significantly differentially expressed circRNAs (DEC): 115 upregulated (red dots) and 22 downregulated (blue dots). Analysis was performed using GEO2R software, with the p -value threshold at <0.05 and log fold changes (FC) at >1. ( E ) Heatmap for the 12 thyroid tissue specimens using the 137 differentially expressed circRNAs. There was an upregulation pattern of genes in patient samples. Clear differentiation of four PTC tissues and incomplete separation of two others are shown. ( F ) Principal component analysis to visualize how samples are related to each other. By using the deregulated genes, a complete demarcation was observed between PTC and normal tissues. Axes 1 and 2 explain 66.6% and 9.7% of the variability, respectively. ( G ) The top-up and downregulated circRNAs in PTC tissues. Derived protein-coding genes from which circRNAs were formed are shown. Fold change values are depicted at the end of the bars. ( H ) Frequency of tested circRNAs in the microarray according to their chromosomal localization. Y axis is log10 transformed, and the X axis represents the human chromosomes with removed missing chromosomes (chromosomes 18, 21, and Y). ( I ) Chromosomal ideograms represent the differentially expressed circRNAs annotated with lines in color at specific base-pair locations: blue for upregulated DECs and green for downregulated DECs.
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    <t>Microarray</t> transcriptomic signature of circRNAs in human papillary thyroid carcinoma. ( A ) Characteristics of six PTC patients were retrieved from the Gene Expression Omnibus database (GSE93522). PTC was compared with their paired contralateral normal thyroid tissues ( B ) Boxplots showing the distribution of the values of the selected samples. Median-centered values are indicated after log transform and quantile normalization. ( C ) Principal component analysis for data exploration. The geometrical projection for samples is based on the similarities and differences in the expression of 2895 circRNAs. Samples are plotted across two coordinates; axis 1 explained 52.1% of the variance, whereas axis 2 demonstrated 17% of the data variability. ( D ) Volcano plot displays statistical significance (−log10 p -value) versus magnitude of change (log2 fold change) in PTC compared with controls. Each dot represents a circRNA. The plot shows 137 significantly differentially expressed circRNAs (DEC): 115 upregulated (red dots) and 22 downregulated (blue dots). Analysis was performed using GEO2R software, with the p -value threshold at <0.05 and log fold changes (FC) at >1. ( E ) Heatmap for the 12 thyroid tissue specimens using the 137 differentially expressed circRNAs. There was an upregulation pattern of genes in patient samples. Clear differentiation of four PTC tissues and incomplete separation of two others are shown. ( F ) Principal component analysis to visualize how samples are related to each other. By using the deregulated genes, a complete demarcation was observed between PTC and normal tissues. Axes 1 and 2 explain 66.6% and 9.7% of the variability, respectively. ( G ) The top-up and downregulated circRNAs in PTC tissues. Derived protein-coding genes from which circRNAs were formed are shown. Fold change values are depicted at the end of the bars. ( H ) Frequency of tested circRNAs in the microarray according to their chromosomal localization. Y axis is log10 transformed, and the X axis represents the human chromosomes with removed missing chromosomes (chromosomes 18, 21, and Y). ( I ) Chromosomal ideograms represent the differentially expressed circRNAs annotated with lines in color at specific base-pair locations: blue for upregulated DECs and green for downregulated DECs.
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    Image Search Results


    Microarray transcriptomic signature of circRNAs in human papillary thyroid carcinoma. ( A ) Characteristics of six PTC patients were retrieved from the Gene Expression Omnibus database (GSE93522). PTC was compared with their paired contralateral normal thyroid tissues ( B ) Boxplots showing the distribution of the values of the selected samples. Median-centered values are indicated after log transform and quantile normalization. ( C ) Principal component analysis for data exploration. The geometrical projection for samples is based on the similarities and differences in the expression of 2895 circRNAs. Samples are plotted across two coordinates; axis 1 explained 52.1% of the variance, whereas axis 2 demonstrated 17% of the data variability. ( D ) Volcano plot displays statistical significance (−log10 p -value) versus magnitude of change (log2 fold change) in PTC compared with controls. Each dot represents a circRNA. The plot shows 137 significantly differentially expressed circRNAs (DEC): 115 upregulated (red dots) and 22 downregulated (blue dots). Analysis was performed using GEO2R software, with the p -value threshold at <0.05 and log fold changes (FC) at >1. ( E ) Heatmap for the 12 thyroid tissue specimens using the 137 differentially expressed circRNAs. There was an upregulation pattern of genes in patient samples. Clear differentiation of four PTC tissues and incomplete separation of two others are shown. ( F ) Principal component analysis to visualize how samples are related to each other. By using the deregulated genes, a complete demarcation was observed between PTC and normal tissues. Axes 1 and 2 explain 66.6% and 9.7% of the variability, respectively. ( G ) The top-up and downregulated circRNAs in PTC tissues. Derived protein-coding genes from which circRNAs were formed are shown. Fold change values are depicted at the end of the bars. ( H ) Frequency of tested circRNAs in the microarray according to their chromosomal localization. Y axis is log10 transformed, and the X axis represents the human chromosomes with removed missing chromosomes (chromosomes 18, 21, and Y). ( I ) Chromosomal ideograms represent the differentially expressed circRNAs annotated with lines in color at specific base-pair locations: blue for upregulated DECs and green for downregulated DECs.

    Journal: Cancers

    Article Title: A Review and In Silico Analysis of Tissue and Exosomal Circular RNAs: Opportunities and Challenges in Thyroid Cancer

    doi: 10.3390/cancers14194728

    Figure Lengend Snippet: Microarray transcriptomic signature of circRNAs in human papillary thyroid carcinoma. ( A ) Characteristics of six PTC patients were retrieved from the Gene Expression Omnibus database (GSE93522). PTC was compared with their paired contralateral normal thyroid tissues ( B ) Boxplots showing the distribution of the values of the selected samples. Median-centered values are indicated after log transform and quantile normalization. ( C ) Principal component analysis for data exploration. The geometrical projection for samples is based on the similarities and differences in the expression of 2895 circRNAs. Samples are plotted across two coordinates; axis 1 explained 52.1% of the variance, whereas axis 2 demonstrated 17% of the data variability. ( D ) Volcano plot displays statistical significance (−log10 p -value) versus magnitude of change (log2 fold change) in PTC compared with controls. Each dot represents a circRNA. The plot shows 137 significantly differentially expressed circRNAs (DEC): 115 upregulated (red dots) and 22 downregulated (blue dots). Analysis was performed using GEO2R software, with the p -value threshold at <0.05 and log fold changes (FC) at >1. ( E ) Heatmap for the 12 thyroid tissue specimens using the 137 differentially expressed circRNAs. There was an upregulation pattern of genes in patient samples. Clear differentiation of four PTC tissues and incomplete separation of two others are shown. ( F ) Principal component analysis to visualize how samples are related to each other. By using the deregulated genes, a complete demarcation was observed between PTC and normal tissues. Axes 1 and 2 explain 66.6% and 9.7% of the variability, respectively. ( G ) The top-up and downregulated circRNAs in PTC tissues. Derived protein-coding genes from which circRNAs were formed are shown. Fold change values are depicted at the end of the bars. ( H ) Frequency of tested circRNAs in the microarray according to their chromosomal localization. Y axis is log10 transformed, and the X axis represents the human chromosomes with removed missing chromosomes (chromosomes 18, 21, and Y). ( I ) Chromosomal ideograms represent the differentially expressed circRNAs annotated with lines in color at specific base-pair locations: blue for upregulated DECs and green for downregulated DECs.

    Article Snippet: The platform used was “GPL19978 Agilent-069978 Arraystar Human CircRNA microarray V1”.

    Techniques: Microarray, Expressing, Software, Derivative Assay, Transformation Assay