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human microrna (mirna) microarray v1.0  (Agilent technologies)


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    Agilent technologies human microrna (mirna) microarray v1.0
    Weighted gene correlation network analysis of sputum <t>microRNA</t> expression and asthma features (n = 78 samples). Using expressed microRNAs (n = 221) in the sputum, six modules were identified. These modules had correlations with multiple demographic, clinical, physiologic, and sputum characteristics. Positive correlations are red, and negative correlations are blue. The microRNAs in the blue (nely) module were positively associated with age, asthma duration, hospitalizations in the previous year, bronchodilator response, and neutrophil and lymphocyte cell counts in the sputum; and negatively correlated with asthma quality of life (AQLQ), FEV1% predicted, and FVC% predicted at baseline. Values are correlation coefficient (nominal P value). BDR = bronchodilator response; Eos = eosinophil; FeNO = fractional exhaled nitric oxide; Lymph = lymphocyte; Mac = <t>macrophage;</t> <t>miRNA</t> = microRNA; Neu = neutrophil.
    Human Microrna (Mirna) Microarray V1.0, 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/human+microrna+microarray+v1%2E0/pmc07328332-182-8-13
    Average 90 stars, based on 1 article reviews
    human microrna (mirna) microarray v1.0 - by Bioz Stars, 2026-09
    90/100 stars

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    1) Product Images from "A Network of Sputum MicroRNAs Is Associated with Neutrophilic Airway Inflammation in Asthma"

    Article Title: A Network of Sputum MicroRNAs Is Associated with Neutrophilic Airway Inflammation in Asthma

    Journal: American Journal of Respiratory and Critical Care Medicine

    doi: 10.1164/rccm.201912-2360OC

    Weighted gene correlation network analysis of sputum microRNA expression and asthma features (n = 78 samples). Using expressed microRNAs (n = 221) in the sputum, six modules were identified. These modules had correlations with multiple demographic, clinical, physiologic, and sputum characteristics. Positive correlations are red, and negative correlations are blue. The microRNAs in the blue (nely) module were positively associated with age, asthma duration, hospitalizations in the previous year, bronchodilator response, and neutrophil and lymphocyte cell counts in the sputum; and negatively correlated with asthma quality of life (AQLQ), FEV1% predicted, and FVC% predicted at baseline. Values are correlation coefficient (nominal P value). BDR = bronchodilator response; Eos = eosinophil; FeNO = fractional exhaled nitric oxide; Lymph = lymphocyte; Mac = macrophage; miRNA = microRNA; Neu = neutrophil.
    Figure Legend Snippet: Weighted gene correlation network analysis of sputum microRNA expression and asthma features (n = 78 samples). Using expressed microRNAs (n = 221) in the sputum, six modules were identified. These modules had correlations with multiple demographic, clinical, physiologic, and sputum characteristics. Positive correlations are red, and negative correlations are blue. The microRNAs in the blue (nely) module were positively associated with age, asthma duration, hospitalizations in the previous year, bronchodilator response, and neutrophil and lymphocyte cell counts in the sputum; and negatively correlated with asthma quality of life (AQLQ), FEV1% predicted, and FVC% predicted at baseline. Values are correlation coefficient (nominal P value). BDR = bronchodilator response; Eos = eosinophil; FeNO = fractional exhaled nitric oxide; Lymph = lymphocyte; Mac = macrophage; miRNA = microRNA; Neu = neutrophil.

    Techniques Used: Expressing

    Weighted gene correlation network analysis of microRNA (miR) and mRNA expression in matched sputum samples (n = 21). Weighted gene correlation network analysis heatmap of the correlation between genes expressed in the sputum (n = 16,966). This analysis identified 32 gene modules correlated with the 12 microRNAs included in the nely microRNA module in paired mRNA and microRNA samples obtained from the same individuals. Positive correlations are red, and negative correlations are blue. Two modules had the most positive and negative correlations. The lightcyan mRNA module had positive correlations with 10 nely module microRNAs, and the turquoise module had negative correlations with 8 nely module microRNAs. Gene enrichment analysis of the lightcyan mRNA module revealed enrichment for TLR (Toll-like receptor) pathways and T-helper cell type 17 pathways, and the turquoise mRNA module was enriched for the unfolded protein response (UPR). These putative biological functions for the two modules are highlighted in the module. Values are correlation coefficient (nominal P value).
    Figure Legend Snippet: Weighted gene correlation network analysis of microRNA (miR) and mRNA expression in matched sputum samples (n = 21). Weighted gene correlation network analysis heatmap of the correlation between genes expressed in the sputum (n = 16,966). This analysis identified 32 gene modules correlated with the 12 microRNAs included in the nely microRNA module in paired mRNA and microRNA samples obtained from the same individuals. Positive correlations are red, and negative correlations are blue. Two modules had the most positive and negative correlations. The lightcyan mRNA module had positive correlations with 10 nely module microRNAs, and the turquoise module had negative correlations with 8 nely module microRNAs. Gene enrichment analysis of the lightcyan mRNA module revealed enrichment for TLR (Toll-like receptor) pathways and T-helper cell type 17 pathways, and the turquoise mRNA module was enriched for the unfolded protein response (UPR). These putative biological functions for the two modules are highlighted in the module. Values are correlation coefficient (nominal P value).

    Techniques Used: Expressing

    Related Articles

    Labeling:

    Article Title: A microRNA survival signature (MiSS) for advanced ovarian cancer.
    Article Snippet: Contents lists available at ScienceDirect Gynecologic Oncology j ourna l homepage: www.e lsev ie r.com/ locate /ygyno A microRNA survival signature (MiSS) for advanced ovarian cancer☆,☆☆ Karin K. Shih a, Li-Xuan Qin b, Edward J. Tanner a, Qin Zhou b, Maria Bisogna a, Fanny Dao a, Narciso Olvera a, Agnes Viale c, Richard R. Barakat a, Douglas A. Levine a,⁎ a Gynecology Service, Department of Surgery, Memorial Sloan-Kettering Cancer Center, USA b Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, USA c Genomics Core Laboratory, Memorial Sloan-Kettering Cancer Center, USA ☆ Supported in part by the Anne B. Kingsley Ovarian C the Gynecologic Cancer Foundation, Entertainment Ind Walk for Women, and Callaway Golf Foundation Wome ☆☆ Presented at the 40th Annual Meeting of the Socie San Antonio, Texas.. ⁎ Corresponding author at: Gynecology Service, Dep Sloan-Kettering Cancer Center, 1275 York Ave, New Yor 717 3214.. E-mail address: gynbreast@mskcc.org (D.A.

    Microarray:

    Article Title: A microRNA survival signature (MiSS) for advanced ovarian cancer.
    Article Snippet: Contents lists available at ScienceDirect Gynecologic Oncology j ourna l homepage: www.e lsev ie r.com/ locate /ygyno A microRNA survival signature (MiSS) for advanced ovarian cancer☆,☆☆ Karin K. Shih a, Li-Xuan Qin b, Edward J. Tanner a, Qin Zhou b, Maria Bisogna a, Fanny Dao a, Narciso Olvera a, Agnes Viale c, Richard R. Barakat a, Douglas A. Levine a,⁎ a Gynecology Service, Department of Surgery, Memorial Sloan-Kettering Cancer Center, USA b Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, USA c Genomics Core Laboratory, Memorial Sloan-Kettering Cancer Center, USA ☆ Supported in part by the Anne B. Kingsley Ovarian C the Gynecologic Cancer Foundation, Entertainment Ind Walk for Women, and Callaway Golf Foundation Wome ☆☆ Presented at the 40th Annual Meeting of the Socie San Antonio, Texas.. ⁎ Corresponding author at: Gynecology Service, Dep Sloan-Kettering Cancer Center, 1275 York Ave, New Yor 717 3214.. E-mail address: gynbreast@mskcc.org (D.A.



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    Weighted gene correlation network analysis of sputum <t>microRNA</t> expression and asthma features (n = 78 samples). Using expressed microRNAs (n = 221) in the sputum, six modules were identified. These modules had correlations with multiple demographic, clinical, physiologic, and sputum characteristics. Positive correlations are red, and negative correlations are blue. The microRNAs in the blue (nely) module were positively associated with age, asthma duration, hospitalizations in the previous year, bronchodilator response, and neutrophil and lymphocyte cell counts in the sputum; and negatively correlated with asthma quality of life (AQLQ), FEV1% predicted, and FVC% predicted at baseline. Values are correlation coefficient (nominal P value). BDR = bronchodilator response; Eos = eosinophil; FeNO = fractional exhaled nitric oxide; Lymph = lymphocyte; Mac = <t>macrophage;</t> <t>miRNA</t> = microRNA; Neu = neutrophil.
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    Image Search Results


    Weighted gene correlation network analysis of sputum microRNA expression and asthma features (n = 78 samples). Using expressed microRNAs (n = 221) in the sputum, six modules were identified. These modules had correlations with multiple demographic, clinical, physiologic, and sputum characteristics. Positive correlations are red, and negative correlations are blue. The microRNAs in the blue (nely) module were positively associated with age, asthma duration, hospitalizations in the previous year, bronchodilator response, and neutrophil and lymphocyte cell counts in the sputum; and negatively correlated with asthma quality of life (AQLQ), FEV1% predicted, and FVC% predicted at baseline. Values are correlation coefficient (nominal P value). BDR = bronchodilator response; Eos = eosinophil; FeNO = fractional exhaled nitric oxide; Lymph = lymphocyte; Mac = macrophage; miRNA = microRNA; Neu = neutrophil.

    Journal: American Journal of Respiratory and Critical Care Medicine

    Article Title: A Network of Sputum MicroRNAs Is Associated with Neutrophilic Airway Inflammation in Asthma

    doi: 10.1164/rccm.201912-2360OC

    Figure Lengend Snippet: Weighted gene correlation network analysis of sputum microRNA expression and asthma features (n = 78 samples). Using expressed microRNAs (n = 221) in the sputum, six modules were identified. These modules had correlations with multiple demographic, clinical, physiologic, and sputum characteristics. Positive correlations are red, and negative correlations are blue. The microRNAs in the blue (nely) module were positively associated with age, asthma duration, hospitalizations in the previous year, bronchodilator response, and neutrophil and lymphocyte cell counts in the sputum; and negatively correlated with asthma quality of life (AQLQ), FEV1% predicted, and FVC% predicted at baseline. Values are correlation coefficient (nominal P value). BDR = bronchodilator response; Eos = eosinophil; FeNO = fractional exhaled nitric oxide; Lymph = lymphocyte; Mac = macrophage; miRNA = microRNA; Neu = neutrophil.

    Article Snippet: RNA was labeled and hybridized to the Agilent Human microRNA (miRNA) Microarray v1.0 (Agilent Technologies).

    Techniques: Expressing

    Weighted gene correlation network analysis of microRNA (miR) and mRNA expression in matched sputum samples (n = 21). Weighted gene correlation network analysis heatmap of the correlation between genes expressed in the sputum (n = 16,966). This analysis identified 32 gene modules correlated with the 12 microRNAs included in the nely microRNA module in paired mRNA and microRNA samples obtained from the same individuals. Positive correlations are red, and negative correlations are blue. Two modules had the most positive and negative correlations. The lightcyan mRNA module had positive correlations with 10 nely module microRNAs, and the turquoise module had negative correlations with 8 nely module microRNAs. Gene enrichment analysis of the lightcyan mRNA module revealed enrichment for TLR (Toll-like receptor) pathways and T-helper cell type 17 pathways, and the turquoise mRNA module was enriched for the unfolded protein response (UPR). These putative biological functions for the two modules are highlighted in the module. Values are correlation coefficient (nominal P value).

    Journal: American Journal of Respiratory and Critical Care Medicine

    Article Title: A Network of Sputum MicroRNAs Is Associated with Neutrophilic Airway Inflammation in Asthma

    doi: 10.1164/rccm.201912-2360OC

    Figure Lengend Snippet: Weighted gene correlation network analysis of microRNA (miR) and mRNA expression in matched sputum samples (n = 21). Weighted gene correlation network analysis heatmap of the correlation between genes expressed in the sputum (n = 16,966). This analysis identified 32 gene modules correlated with the 12 microRNAs included in the nely microRNA module in paired mRNA and microRNA samples obtained from the same individuals. Positive correlations are red, and negative correlations are blue. Two modules had the most positive and negative correlations. The lightcyan mRNA module had positive correlations with 10 nely module microRNAs, and the turquoise module had negative correlations with 8 nely module microRNAs. Gene enrichment analysis of the lightcyan mRNA module revealed enrichment for TLR (Toll-like receptor) pathways and T-helper cell type 17 pathways, and the turquoise mRNA module was enriched for the unfolded protein response (UPR). These putative biological functions for the two modules are highlighted in the module. Values are correlation coefficient (nominal P value).

    Article Snippet: RNA was labeled and hybridized to the Agilent Human microRNA (miRNA) Microarray v1.0 (Agilent Technologies).

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    Figure Lengend Snippet: Common significant signaling pathways using DIANA-miRPath analysis of miRNAs selected by DDSS, SWVg and K-means methods

    Article Snippet: The miRNA expression dataset was generated using the Agilent Human MicroRNA Microarray Platform 8X15K, V1.0 (beta version of G4470A) based on the Sanger Database 9.1.

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