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Integrative modeling reveals the principles of multi-scale chromatin boundary formation in human nuclear organization

Overview of attention for article published in Genome Biology, May 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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19 X users
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1 Facebook page
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1 Google+ user

Citations

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39 Dimensions

Readers on

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107 Mendeley
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4 CiteULike
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Title
Integrative modeling reveals the principles of multi-scale chromatin boundary formation in human nuclear organization
Published in
Genome Biology, May 2015
DOI 10.1186/s13059-015-0661-x
Pubmed ID
Authors

Benjamin L Moore, Stuart Aitken, Colin A Semple

Abstract

Interphase chromosomes adopt a hierarchical structure, and recent data have characterized their chromatin organization at very different scales, from sub-genic regions associated with DNA-binding proteins at the order of tens or hundreds of bases, through larger regions with active or repressed chromatin states, up to multi-megabase-scale domains associated with nuclear positioning, replication timing and other qualities. However, we have lacked detailed, quantitative models to understand the interactions between these different strata. Here we collate large collections of matched locus-level chromatin features and Hi-C interaction data, representing higher-order organization, across three human cell types. We use quantitative modeling approaches to assess whether locus-level features are sufficient to explain higher-order structure, and identify the most influential underlying features. We identify structurally variable domains between cell types and examine the underlying features to discover a general association with cell-type-specific enhancer activity. We also identify the most prominent features marking the boundaries of two types of higher-order domains at different scales: topologically associating domains and nuclear compartments. We find parallel enrichments of particular chromatin features for both types, including features associated with active promoters and the architectural proteins CTCF and YY1. We show that integrative modeling of large chromatin dataset collections using random forests can generate useful insights into chromosome structure. The models produced recapitulate known biological features of the cell types involved, allow exploration of the antecedents of higher-order structures and generate testable hypotheses for further experimental studies.

X Demographics

X Demographics

The data shown below were collected from the profiles of 19 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 107 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 2%
United Kingdom 2 2%
Canada 1 <1%
Russia 1 <1%
Spain 1 <1%
Unknown 100 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 30 28%
Researcher 25 23%
Student > Master 10 9%
Student > Bachelor 8 7%
Professor 8 7%
Other 19 18%
Unknown 7 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 45 42%
Biochemistry, Genetics and Molecular Biology 34 32%
Computer Science 10 9%
Medicine and Dentistry 4 4%
Mathematics 3 3%
Other 4 4%
Unknown 7 7%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 29 May 2015.
All research outputs
#3,202,147
of 25,373,627 outputs
Outputs from Genome Biology
#2,331
of 4,467 outputs
Outputs of similar age
#39,418
of 280,163 outputs
Outputs of similar age from Genome Biology
#40
of 65 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one is in the 47th percentile – i.e., 47% 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 280,163 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 65 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.