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CpG Islands

Overview of attention for book
Cover of 'CpG Islands'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 CpG Islands: A Historical Perspective
  3. Altmetric Badge
    Chapter 2 Biochemical Identification of Nonmethylated DNA by BioCAP-Seq
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    Chapter 3 Prediction of CpG Islands as an Intrinsic Clustering Property Found in Many Eukaryotic DNA Sequences and Its Relation to DNA Methylation
  5. Altmetric Badge
    Chapter 4 CpG Islands in Cancer: Heads, Tails, and Sides
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    Chapter 5 Infinium DNA Methylation Microarrays on Formalin-Fixed, Paraffin-Embedded Samples
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    Chapter 6 The Use of Methylation-Sensitive Multiplex Ligation-Dependent Probe Amplification for Quantification of Imprinted Methylation
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    Chapter 7 The Pancancer DNA Methylation Trackhub: A Window to The Cancer Genome Atlas Epigenomics Data
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    Chapter 8 Methylation-Sensitive Amplification Length Polymorphism (MS-AFLP) Microarrays for Epigenetic Analysis of Human Genomes
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    Chapter 9 Genome-Wide Profiling of DNA Methyltransferases in Mammalian Cells
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    Chapter 10 Experimental Design and Bioinformatic Analysis of DNA Methylation Data
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    Chapter 11 Assay for Transposase Accessible Chromatin (ATAC-Seq) to Chart the Open Chromatin Landscape of Human Pancreatic Islets
  13. Altmetric Badge
    Chapter 12 Defining Regulatory Elements in the Human Genome Using Nucleosome Occupancy and Methylome Sequencing (NOMe-Seq)
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    Chapter 13 Genome-Wide Mapping of Protein–DNA Interactions on Nascent Chromatin
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    Chapter 14 Analysis of Chromatin Interactions Mediated by Specific Architectural Proteins in Drosophila Cells
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    Chapter 15 High-Throughput Single-Cell RNA Sequencing and Data Analysis
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    Chapter 16 Functional Insulator Scanning of CpG Islands to Identify Regulatory Regions of Promoters Using CRISPR
  18. Altmetric Badge
    Chapter 17 An Application-Directed, Versatile DNA FISH Platform for Research and Diagnostics
Attention for Chapter 9: Genome-Wide Profiling of DNA Methyltransferases in Mammalian Cells
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (74th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

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Chapter title
Genome-Wide Profiling of DNA Methyltransferases in Mammalian Cells
Chapter number 9
Book title
CpG Islands
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7768-0_9
Pubmed ID
Book ISBNs
978-1-4939-7767-3, 978-1-4939-7768-0
Authors

Massimiliano Manzo, Christina Ambrosi, Tuncay Baubec

Abstract

Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is currently the method of choice to determine binding sites of chromatin-associated factors in a genome-wide manner. Here, we describe a method to investigate the binding preferences of mammalian DNA methyltransferases (DNMT) based on ChIP-seq using biotin-tagging. Stringent ChIP of DNMT proteins based on the strong interaction between biotin and avidin circumvents limitations arising from low antibody specificity and ensures reproducible enrichment. DNMT-bound DNA fragments are ligated to sequencing adaptors, amplified and sequenced on a high-throughput sequencing instrument. Bioinformatic analysis gives valuable information about the binding preferences of DNMTs genome-wide and around promoter regions. This method is unconventional due to the use of genetically engineered cells; however, it allows specific and reliable determination of DNMT binding.

X Demographics

X Demographics

The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 31%
Student > Bachelor 2 15%
Other 1 8%
Student > Ph. D. Student 1 8%
Student > Doctoral Student 1 8%
Other 2 15%
Unknown 2 15%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 62%
Neuroscience 1 8%
Chemistry 1 8%
Medicine and Dentistry 1 8%
Unknown 2 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 May 2018.
All research outputs
#6,098,903
of 24,514,423 outputs
Outputs from Methods in molecular biology
#1,659
of 13,803 outputs
Outputs of similar age
#114,288
of 452,050 outputs
Outputs of similar age from Methods in molecular biology
#141
of 1,483 outputs
Altmetric has tracked 24,514,423 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 13,803 research outputs from this source. They receive a mean Attention Score of 3.5. This one has done well, scoring higher than 87% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 452,050 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 1,483 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.