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metabric dna microarray datasets  (Thermo Fisher)


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    Thermo Fisher metabric dna microarray datasets
    Metabric Dna Microarray Datasets, supplied by Thermo Fisher, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/datasets+of+dna+microarray/DNA/pm41686639-557-27-26
    Average 99 stars, based on 1 article reviews
    metabric dna microarray datasets - by Bioz Stars, 2026-09
    99/100 stars

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    Article Title: SPP1 and AGER as potential prognostic biomarkers for lung adenocarcinoma
    Article Snippet: Datasets GSE10072 and GSE7670 were employed for the identification of DEGs on the Affymetrix Gene Chip TM Human Genome U133A arrayplatform (Affymetrix; Thermo Fisher Scientific, Inc., Waltham, MA, USA).

    Article Title: NKL homeobox gene NKX2-2 is aberrantly expressed in Hodgkin lymphoma
    Article Snippet: Expression profiling datasets of seven HL cell lines using HG U133 Plus 2.0 gene chip (Affymetrix) were generated by Prof. Andreas Rosenwald (Institute of Pathology, University of Würzburg, Germany) and by Dr. Robert Geffers (Genome Analytics, Helmholtz Centre for Infection Research, Braunschweig, Germany).

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    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