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Predicting the three-dimensional folding of cis-regulatory regions in mammalian genomes using bioinformatic data and polymer models

Overview of attention for article published in Genome Biology, March 2016
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  • Good Attention Score compared to outputs of the same age (69th percentile)

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8 X users

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132 Mendeley
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2 CiteULike
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Title
Predicting the three-dimensional folding of cis-regulatory regions in mammalian genomes using bioinformatic data and polymer models
Published in
Genome Biology, March 2016
DOI 10.1186/s13059-016-0909-0
Pubmed ID
Authors

Chris A. Brackley, Jill M. Brown, Dominic Waithe, Christian Babbs, James Davies, Jim R. Hughes, Veronica J. Buckle, Davide Marenduzzo

Abstract

The three-dimensional (3D) organization of chromosomes can be probed using methods like Capture-C. However, it is unclear how such population-level data relate to the organization within a single cell, and the mechanisms leading to the observed interactions are still largely obscure. We present a polymer modeling scheme based on the assumption that chromosome architecture is maintained by protein bridges, which form chromatin loops. To test the model, we perform FISH experiments and compare with Capture-C data. Starting merely from the locations of protein binding sites, our model accurately predicts the experimentally observed chromatin interactions, revealing a population of 3D conformations.

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 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 132 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
United Kingdom 1 <1%
Norway 1 <1%
Unknown 128 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 40 30%
Researcher 35 27%
Student > Bachelor 10 8%
Student > Doctoral Student 8 6%
Professor 7 5%
Other 11 8%
Unknown 21 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 44 33%
Biochemistry, Genetics and Molecular Biology 37 28%
Physics and Astronomy 13 10%
Computer Science 8 6%
Engineering 5 4%
Other 5 4%
Unknown 20 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 18 May 2016.
All research outputs
#7,205,554
of 25,374,917 outputs
Outputs from Genome Biology
#3,269
of 4,467 outputs
Outputs of similar age
#96,203
of 315,347 outputs
Outputs of similar age from Genome Biology
#69
of 79 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
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 26th percentile – i.e., 26% 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 315,347 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 69% of its contemporaries.
We're also able to compare this research output to 79 others from the same source and published within six weeks on either side of this one. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.