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van de vijver dna microarray dataset  (Rosetta Inpharmatics)

 
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    Rosetta Inpharmatics van de vijver dna microarray dataset
    Van De Vijver Dna Microarray Dataset, supplied by Rosetta Inpharmatics, 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/dna+microarray+dataset/van+de+vijver+dna+microarray+dataset/pm19533747-43-1-10
    Average 90 stars, based on 1 article reviews
    van de vijver dna microarray dataset - by Bioz Stars, 2026-09
    90/100 stars

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    Related Articles

    Microarray:

    Article Title: JAM-A expression positively correlates with poor prognosis in breast cancer patients.
    Article Snippet: Elaine A. McSherry, Sharon F. McGee, Karin Jirstrom, Emma M. Doyle, Donal J. Brennan, Goran Landberg, Peter A. Dervan, Ann M. Hopkins* and William M. Gallagher UCD School of Biomolecular and Biomedical Science, UCD Conway Institute, University College Dublin, Ireland Division of Pathology, Department of Laboratory Medicine, Lund University, Malmo University Hospital, Sweden UCD School of Medicine and Medical Science and Mater Misericordiae Hospital, Dublin, Ireland Department of Surgery, Royal College of Surgeons in Ireland, Dublin, Ireland



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    Image Search Results


    Low-dimensional representation of variable DNA methylation sites across all placental and immune cell types and whole placental tissue samples shows samples cluster by cell type.

    Journal: Epigenetics

    Article Title: Placental and immune cell DNA methylation reference panel for bulk tissue cell composition estimation in epidemiological studies

    doi: 10.1080/15592294.2024.2437275

    Figure Lengend Snippet: Low-dimensional representation of variable DNA methylation sites across all placental and immune cell types and whole placental tissue samples shows samples cluster by cell type.

    Article Snippet: To assess the performance of our placental DNA methylation deconvolution reference, we compared its ability to predict DNA methylation variation [ ] in a preprocessed placental whole tissue Illumina EPIC microarray DNA methylation dataset comprising 204 placentas across three cohorts (GEO accession number GSE232778) [ ] against the only existing multi-cell type reference [ ].

    Techniques: DNA Methylation Assay

    Analytic table of DNA methylation samples used for deconvolution reference.

    Journal: Epigenetics

    Article Title: Placental and immune cell DNA methylation reference panel for bulk tissue cell composition estimation in epidemiological studies

    doi: 10.1080/15592294.2024.2437275

    Figure Lengend Snippet: Analytic table of DNA methylation samples used for deconvolution reference.

    Article Snippet: To assess the performance of our placental DNA methylation deconvolution reference, we compared its ability to predict DNA methylation variation [ ] in a preprocessed placental whole tissue Illumina EPIC microarray DNA methylation dataset comprising 204 placentas across three cohorts (GEO accession number GSE232778) [ ] against the only existing multi-cell type reference [ ].

    Techniques: DNA Methylation Assay, Fluorescence

    Placental cell type differential DNA methylation. Volcano plots comparing site-specific DNA methylation levels in one cell type against the average across all other cell types.

    Journal: Epigenetics

    Article Title: Placental and immune cell DNA methylation reference panel for bulk tissue cell composition estimation in epidemiological studies

    doi: 10.1080/15592294.2024.2437275

    Figure Lengend Snippet: Placental cell type differential DNA methylation. Volcano plots comparing site-specific DNA methylation levels in one cell type against the average across all other cell types.

    Article Snippet: To assess the performance of our placental DNA methylation deconvolution reference, we compared its ability to predict DNA methylation variation [ ] in a preprocessed placental whole tissue Illumina EPIC microarray DNA methylation dataset comprising 204 placentas across three cohorts (GEO accession number GSE232778) [ ] against the only existing multi-cell type reference [ ].

    Techniques: DNA Methylation Assay

    Top differentially methylated sites unique to the five placental cell types (cytotrophoblast, endothelial, Hofbauer, stromal, and syncytiotrophoblast) and nucleated red blood cells with gene annotations reveal highly specific DNA methylation profiles by cell type.

    Journal: Epigenetics

    Article Title: Placental and immune cell DNA methylation reference panel for bulk tissue cell composition estimation in epidemiological studies

    doi: 10.1080/15592294.2024.2437275

    Figure Lengend Snippet: Top differentially methylated sites unique to the five placental cell types (cytotrophoblast, endothelial, Hofbauer, stromal, and syncytiotrophoblast) and nucleated red blood cells with gene annotations reveal highly specific DNA methylation profiles by cell type.

    Article Snippet: To assess the performance of our placental DNA methylation deconvolution reference, we compared its ability to predict DNA methylation variation [ ] in a preprocessed placental whole tissue Illumina EPIC microarray DNA methylation dataset comprising 204 placentas across three cohorts (GEO accession number GSE232778) [ ] against the only existing multi-cell type reference [ ].

    Techniques: Methylation, DNA Methylation Assay

    Summary graphs of the root mean square error of prediction in the ability to model principal components of DNA methylation in 204 placenta dataset GSE232778 for our expanded reference versus the existing reference implemented in planet from 1,000 repeats of a 10-fold cross-validation linear regression model with estimated cell composition as the predictor variables.

    Journal: Epigenetics

    Article Title: Placental and immune cell DNA methylation reference panel for bulk tissue cell composition estimation in epidemiological studies

    doi: 10.1080/15592294.2024.2437275

    Figure Lengend Snippet: Summary graphs of the root mean square error of prediction in the ability to model principal components of DNA methylation in 204 placenta dataset GSE232778 for our expanded reference versus the existing reference implemented in planet from 1,000 repeats of a 10-fold cross-validation linear regression model with estimated cell composition as the predictor variables.

    Article Snippet: To assess the performance of our placental DNA methylation deconvolution reference, we compared its ability to predict DNA methylation variation [ ] in a preprocessed placental whole tissue Illumina EPIC microarray DNA methylation dataset comprising 204 placentas across three cohorts (GEO accession number GSE232778) [ ] against the only existing multi-cell type reference [ ].

    Techniques: DNA Methylation Assay, Biomarker Discovery