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Chronic Myeloid Leukemia

Overview of attention for book
Cover of 'Chronic Myeloid Leukemia'

Table of Contents

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    Book Overview
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    Chapter 1 Molecular Detection of BCR-ABL in Chronic Myeloid Leukemia
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    Chapter 2 Induction of Chronic Myeloid Leukemia in Mice
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    Chapter 3 CML Mouse Model Generated from Leukemia Stem Cells
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    Chapter 4 Immunological Analyses of Leukemia Stem Cells
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    Chapter 5 Cell Cycle Analysis of CML Stem Cells Using Hoechst 33342 and Propidium Iodide
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    Chapter 6 Histological and In Vivo Microscopic Analysis of the Bone Marrow Microenvironment in a Murine Model of Chronic Myelogenous Leukemia
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    Chapter 7 Chronic Myeloid Leukemia
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    Chapter 8 Tumor Suppressor Analysis in CML
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    Chapter 9 Chronic Myeloid Leukemia
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    Chapter 10 DREAM: A Simple Method for DNA Methylation Profiling by High-throughput Sequencing
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    Chapter 11 Chronic Myeloid Leukemia
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    Chapter 12 Quantitative Proteomics Analysis of Leukemia Cells
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    Chapter 13 A Convenient Cell Culture Model for CML Acquired Resistance Through BCR-ABL Mutations
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    Chapter 14 High-Throughput Screening of Tyrosine Kinase Inhibitor Resistant Genes in CML
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    Chapter 15 Biological Analysis of Human CML Stem Cells; Xenograft Model of Chronic Phase Human Chronic Myeloid Leukemia
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    Chapter 16 New Mouse Models to Investigate the Efficacy of Drug Combinations in Human Chronic Myeloid Leukemia
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    Chapter 17 Chronic Myeloid Leukemia
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    Chapter 18 Chronic Myeloid Leukemia
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    Chapter 19 Single-Cell Cytokine Profiling to Investigate Cellular Functional Diversity in Hematopoietic Malignancies
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    Chapter 20 Erratum to: An Integrative Analysis of microRNA and mRNA Profiling in CML Stem Cells
Attention for Chapter 11: Chronic Myeloid Leukemia
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Chapter title
Chronic Myeloid Leukemia
Chapter number 11
Book title
Chronic Myeloid Leukemia
Published in
Methods in molecular biology, January 2016
DOI 10.1007/978-1-4939-4011-0_11
Pubmed ID
Book ISBNs
978-1-4939-4009-7, 978-1-4939-4011-0
Authors

Anders, Lars, Li, Zhaodong, Lars Anders, Zhaodong Li

Abstract

Many transcription factors, chromatin-associated proteins and regulatory DNA elements are genetically and/or epigenetically altered in cancer, including Chronic Myeloid Leukemia (CML). This leads to deregulation of transcription that is often causally linked to the tumorigenic state. Chromatin-immunoprecipitation coupled with massively parallel DNA sequencing (ChIP-seq) is the key technology to study transcription as it allows in vivo whole-genome mapping of epigenetic modifications and interactions of proteins with DNA or chromatin. However, numerous DNA/chromatin-binding proteins, including EZH2, remain difficult to "ChIP," thus yielding genome-wide binding maps of only suboptimal quality. Here, we describe a ChIP-seq protocol optimized for high-quality protein-genome binding maps that have proven especially useful for studying difficult to 'ChIP' transcription regulatory factors in Chronic Myeloid Leukemia (CML) and related malignancies.

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The data shown below were collected from the profiles of 3 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 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 1 100%
Readers by discipline Count As %
Immunology and Microbiology 1 100%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 02 September 2016.
All research outputs
#15,381,871
of 22,884,315 outputs
Outputs from Methods in molecular biology
#5,350
of 13,131 outputs
Outputs of similar age
#230,986
of 393,711 outputs
Outputs of similar age from Methods in molecular biology
#545
of 1,471 outputs
Altmetric has tracked 22,884,315 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,131 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 44th percentile – i.e., 44% of its peers scored the same or lower than it.
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 393,711 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,471 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.