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Epigenomics ag 450 k methylation array
450 K Methylation Array, supplied by Epigenomics ag, 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/methylation+array/methylation+array/pmc08276451-122-8-7
Average 90 stars, based on 1 article reviews
450 k methylation array - by Bioz Stars, 2026-09
90/100 stars

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Article Title: Unveil Intrahepatic Cholangiocarcinoma Heterogeneity through the Lens of Omics and Multi-Omics Approaches
Article Snippet: Epigenomics , Ex vivo , Methylation-array , Methylation data used to classify tumors; general hypermethylation in iCCA samples , [ ] .

Article Title: Comprehensive multi-omics profiling identifies novel molecular subtypes of pancreatic ductal adenocarcinoma
Article Snippet: 2021 Ju ( n = 146 resectable PDAC patients from TCGA) , mRNA-Seq, mi-RNA-Seq, epigenomics (methylation array), and SNP , KRAS mutation status serves as an essential supplement to MODEL-P subtypes in predicting overall survival , Two prognosis-correlated PDAC subtypes: “aggressive” and “moderate” with different survival outcomes corresponding to DNA damage repair and immune response.

Article Title: Ensemble-based Gene Selection and an Enhanced Deep Multi-Layer Perceptron-based Classification Model for Classifying Alzheimer's disease
Article Snippet: T. N and T. J, “Complete pipeline for In nium(®) Human Methylation 450K BeadChip data processing using subset quantile normalization for accurate DNA methylation estimation,” Epigenomics, vol.

Article Title: Comprehensive multi-omics profiling identifies novel molecular subtypes of pancreatic ductal adenocarcinoma
Article Snippet: 2020 Kong ( n = 161 PDAC) , Genomics (CVN and SNV), epigenomics (methylation array), and transcriptomics , iC1: improved prognosis; enhanced genomic stability; higher immune score; lesser CNV , Four clinically related molecular subtypes.

Article Title: Unveil Intrahepatic Cholangiocarcinoma Heterogeneity through the Lens of Omics and Multi-Omics Approaches
Article Snippet: Epigenomics + Transcriptomics , Ex vivo , 116 , Methylation-Array; Transcriptome-Array , 4 iCCA subtypes are identified according to different escape mechanisms in TME (immune desert, immunogenic, myeloid, and mesenchymal , [ ] .

DNA Methylation Assay:

Article Title: The omics era: a nexus of untapped potential for Mendelian chromatinopathies
Article Snippet: Genomics , DNA sequence , Sanger Sequencing (Sanger et al. ) Whole Genome Sequencing (WGS) (Lionel et al. ) Whole Exome Sequencing (WES) (Lee et al. ) Microarray-based Genotyping . .. Epigenomics , DNA methylation , Methylation Microarrays(Chater-Diehl et al. ), Reduced Representation Bisulfite Sequencing (RRBS) (Meissner et al. ), Whole Genome Bisulfite Sequencing (WGBS) (Olova et al. ), Methyl Cytosine sequencing (MethylC-seq) (Lister et al. ), Methyl DNA ImmunoPrecipitation analyzed by sequencing (MeDIP-seq) (Down et al. ), Methyl-CpG Binding Domain-isolated genomic DNA analyzed by sequencing (MBD-seq) (Serre et al. ) . .. , Genomic coordinates of Histone Post-Translational Modifications or Chromatin-associated proteins , Chromatin ImmunoPrecipitation and Sequencing (ChIP-seq) (Johnson et al. ) .

Methylation:

Article Title: The omics era: a nexus of untapped potential for Mendelian chromatinopathies
Article Snippet: Genomics , DNA sequence , Sanger Sequencing (Sanger et al. ) Whole Genome Sequencing (WGS) (Lionel et al. ) Whole Exome Sequencing (WES) (Lee et al. ) Microarray-based Genotyping . .. Epigenomics , DNA methylation , Methylation Microarrays(Chater-Diehl et al. ), Reduced Representation Bisulfite Sequencing (RRBS) (Meissner et al. ), Whole Genome Bisulfite Sequencing (WGBS) (Olova et al. ), Methyl Cytosine sequencing (MethylC-seq) (Lister et al. ), Methyl DNA ImmunoPrecipitation analyzed by sequencing (MeDIP-seq) (Down et al. ), Methyl-CpG Binding Domain-isolated genomic DNA analyzed by sequencing (MBD-seq) (Serre et al. ) . .. , Genomic coordinates of Histone Post-Translational Modifications or Chromatin-associated proteins , Chromatin ImmunoPrecipitation and Sequencing (ChIP-seq) (Johnson et al. ) .

Article Title: Insights into the molecular landscape of osteoarthritis in human tissues
Article Snippet: Richard et al. [ ▪▪ ] , 2021 , Untargeted , Developmental knee components , Long-bone chondrocytes , Epigenomics , ATAC-seq , Characterization of the open chromatin profile (one developmental sample), followed by evolutionary analyses and comparisons with GWAS results. .. Dunn et al. [ ] , 2019 , Untargeted , – , Blood , Epigenomics , 450k methylation array , 58 osteoarthritis progressors vs. 58 nonprogressors. .. Duffy et al. [ ] , 2020 , Untargeted , Knee , Cartilage , Epigenomics , ChIP-seq , Target-site characterization of cartilage samples of osteoarthritis patients ( n = 3).

Article Title: 2dFDR: a new approach to confounder adjustment substantially increases detection power in omics association studies
Article Snippet: .. C, D Evaluation of 2dFDR on 54 epigenomics (450 K methylation array) datasets from EWAS of various phenotypes (m ≅ 450,000, confounder: cell mixtures). ..

Methylation Sequencing:

Article Title: The omics era: a nexus of untapped potential for Mendelian chromatinopathies
Article Snippet: Genomics , DNA sequence , Sanger Sequencing (Sanger et al. ) Whole Genome Sequencing (WGS) (Lionel et al. ) Whole Exome Sequencing (WES) (Lee et al. ) Microarray-based Genotyping . .. Epigenomics , DNA methylation , Methylation Microarrays(Chater-Diehl et al. ), Reduced Representation Bisulfite Sequencing (RRBS) (Meissner et al. ), Whole Genome Bisulfite Sequencing (WGBS) (Olova et al. ), Methyl Cytosine sequencing (MethylC-seq) (Lister et al. ), Methyl DNA ImmunoPrecipitation analyzed by sequencing (MeDIP-seq) (Down et al. ), Methyl-CpG Binding Domain-isolated genomic DNA analyzed by sequencing (MBD-seq) (Serre et al. ) . .. , Genomic coordinates of Histone Post-Translational Modifications or Chromatin-associated proteins , Chromatin ImmunoPrecipitation and Sequencing (ChIP-seq) (Johnson et al. ) .

Sequencing:

Article Title: The omics era: a nexus of untapped potential for Mendelian chromatinopathies
Article Snippet: Genomics , DNA sequence , Sanger Sequencing (Sanger et al. ) Whole Genome Sequencing (WGS) (Lionel et al. ) Whole Exome Sequencing (WES) (Lee et al. ) Microarray-based Genotyping . .. Epigenomics , DNA methylation , Methylation Microarrays(Chater-Diehl et al. ), Reduced Representation Bisulfite Sequencing (RRBS) (Meissner et al. ), Whole Genome Bisulfite Sequencing (WGBS) (Olova et al. ), Methyl Cytosine sequencing (MethylC-seq) (Lister et al. ), Methyl DNA ImmunoPrecipitation analyzed by sequencing (MeDIP-seq) (Down et al. ), Methyl-CpG Binding Domain-isolated genomic DNA analyzed by sequencing (MBD-seq) (Serre et al. ) . .. , Genomic coordinates of Histone Post-Translational Modifications or Chromatin-associated proteins , Chromatin ImmunoPrecipitation and Sequencing (ChIP-seq) (Johnson et al. ) .

Immunoprecipitation:

Article Title: The omics era: a nexus of untapped potential for Mendelian chromatinopathies
Article Snippet: Genomics , DNA sequence , Sanger Sequencing (Sanger et al. ) Whole Genome Sequencing (WGS) (Lionel et al. ) Whole Exome Sequencing (WES) (Lee et al. ) Microarray-based Genotyping . .. Epigenomics , DNA methylation , Methylation Microarrays(Chater-Diehl et al. ), Reduced Representation Bisulfite Sequencing (RRBS) (Meissner et al. ), Whole Genome Bisulfite Sequencing (WGBS) (Olova et al. ), Methyl Cytosine sequencing (MethylC-seq) (Lister et al. ), Methyl DNA ImmunoPrecipitation analyzed by sequencing (MeDIP-seq) (Down et al. ), Methyl-CpG Binding Domain-isolated genomic DNA analyzed by sequencing (MBD-seq) (Serre et al. ) . .. , Genomic coordinates of Histone Post-Translational Modifications or Chromatin-associated proteins , Chromatin ImmunoPrecipitation and Sequencing (ChIP-seq) (Johnson et al. ) .

Methylated DNA Immunoprecipitation Sequencing:

Article Title: The omics era: a nexus of untapped potential for Mendelian chromatinopathies
Article Snippet: Genomics , DNA sequence , Sanger Sequencing (Sanger et al. ) Whole Genome Sequencing (WGS) (Lionel et al. ) Whole Exome Sequencing (WES) (Lee et al. ) Microarray-based Genotyping . .. Epigenomics , DNA methylation , Methylation Microarrays(Chater-Diehl et al. ), Reduced Representation Bisulfite Sequencing (RRBS) (Meissner et al. ), Whole Genome Bisulfite Sequencing (WGBS) (Olova et al. ), Methyl Cytosine sequencing (MethylC-seq) (Lister et al. ), Methyl DNA ImmunoPrecipitation analyzed by sequencing (MeDIP-seq) (Down et al. ), Methyl-CpG Binding Domain-isolated genomic DNA analyzed by sequencing (MBD-seq) (Serre et al. ) . .. , Genomic coordinates of Histone Post-Translational Modifications or Chromatin-associated proteins , Chromatin ImmunoPrecipitation and Sequencing (ChIP-seq) (Johnson et al. ) .

Binding Assay:

Article Title: The omics era: a nexus of untapped potential for Mendelian chromatinopathies
Article Snippet: Genomics , DNA sequence , Sanger Sequencing (Sanger et al. ) Whole Genome Sequencing (WGS) (Lionel et al. ) Whole Exome Sequencing (WES) (Lee et al. ) Microarray-based Genotyping . .. Epigenomics , DNA methylation , Methylation Microarrays(Chater-Diehl et al. ), Reduced Representation Bisulfite Sequencing (RRBS) (Meissner et al. ), Whole Genome Bisulfite Sequencing (WGBS) (Olova et al. ), Methyl Cytosine sequencing (MethylC-seq) (Lister et al. ), Methyl DNA ImmunoPrecipitation analyzed by sequencing (MeDIP-seq) (Down et al. ), Methyl-CpG Binding Domain-isolated genomic DNA analyzed by sequencing (MBD-seq) (Serre et al. ) . .. , Genomic coordinates of Histone Post-Translational Modifications or Chromatin-associated proteins , Chromatin ImmunoPrecipitation and Sequencing (ChIP-seq) (Johnson et al. ) .



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Image Search Results


( A ) Epigenome-wide association study of dpi in PBMCs based on the entire methylation array. The volcano plots display the −log 10 ( P values) and the directionality of association between CpG sites and infection stages (A, EC, and LC) compared with B: A versus B (left panel), EC versus B (center panel), and LC versus B (right panel). Each dot represents a specific DNAme site. Shown are significantly associated CpG sites ( q < 0.05) with hypomethylation (blue), hypermethylation (red), and nonsignificant (gray). The horizontal axis represents the mean methylation change (i.e., the difference between group means), and the vertical axis represents −log 10 ( P values). ( B ) Changes in EA during each infection stage (A, EC, and LC) relative to B. Biological age analysis was performed based on subsets of clock CpGs. EA at the 3 infection time points was compared with B using mixed-effects linear regression modeling of longitudinal EA changes in PBMCs based on 10 epigenetic clocks. The results are shown separately for young (right) and old (left) RMs. Epigenetic age changes in young (blue) and old (red) RMs are shown. Saturated colors indicate statistically significant changes ( P < 0.05); pale colors indicate nonsignificant changes ( P > 0.05). A statistically significant increase in EA was observed only in young RMs. B–H, Benjamini–Hochberg correction; DMP, differentially methylated positions; dpi, days after infection; RMs, rhesus macaques; B, baseline; A, acute; EC, early chronic; LC, late chronic; EA, epigenetic age.

Journal: The Journal of Clinical Investigation

Article Title: Pathogenic SIV infection is associated with acceleration of epigenetic age in rhesus macaques

doi: 10.1172/JCI189574

Figure Lengend Snippet: ( A ) Epigenome-wide association study of dpi in PBMCs based on the entire methylation array. The volcano plots display the −log 10 ( P values) and the directionality of association between CpG sites and infection stages (A, EC, and LC) compared with B: A versus B (left panel), EC versus B (center panel), and LC versus B (right panel). Each dot represents a specific DNAme site. Shown are significantly associated CpG sites ( q < 0.05) with hypomethylation (blue), hypermethylation (red), and nonsignificant (gray). The horizontal axis represents the mean methylation change (i.e., the difference between group means), and the vertical axis represents −log 10 ( P values). ( B ) Changes in EA during each infection stage (A, EC, and LC) relative to B. Biological age analysis was performed based on subsets of clock CpGs. EA at the 3 infection time points was compared with B using mixed-effects linear regression modeling of longitudinal EA changes in PBMCs based on 10 epigenetic clocks. The results are shown separately for young (right) and old (left) RMs. Epigenetic age changes in young (blue) and old (red) RMs are shown. Saturated colors indicate statistically significant changes ( P < 0.05); pale colors indicate nonsignificant changes ( P > 0.05). A statistically significant increase in EA was observed only in young RMs. B–H, Benjamini–Hochberg correction; DMP, differentially methylated positions; dpi, days after infection; RMs, rhesus macaques; B, baseline; A, acute; EC, early chronic; LC, late chronic; EA, epigenetic age.

Article Snippet: DNAme profiles were generated using a custom Infinium methylation array (HorvathMammalMethylChip40) representing 37,492 CpG highly conserved sites in the mammals, with the NCBI’s Gene Expression Omnibus (GEO) accession number GPL28271 for microarray design ( ).

Techniques: Methylation, Infection