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The three-dimensional genome organization of Drosophila melanogaster through data integration

Overview of attention for article published in Genome Biology, July 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (84th percentile)

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1 blog
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10 X users
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1 Facebook page

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106 Mendeley
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1 CiteULike
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Title
The three-dimensional genome organization of Drosophila melanogaster through data integration
Published in
Genome Biology, July 2017
DOI 10.1186/s13059-017-1264-5
Pubmed ID
Authors

Qingjiao Li, Harianto Tjong, Xiao Li, Ke Gong, Xianghong Jasmine Zhou, Irene Chiolo, Frank Alber

Abstract

Genome structures are dynamic and non-randomly organized in the nucleus of higher eukaryotes. To maximize the accuracy and coverage of three-dimensional genome structural models, it is important to integrate all available sources of experimental information about a genome's organization. It remains a major challenge to integrate such data from various complementary experimental methods. Here, we present an approach for data integration to determine a population of complete three-dimensional genome structures that are statistically consistent with data from both genome-wide chromosome conformation capture (Hi-C) and lamina-DamID experiments. Our structures resolve the genome at the resolution of topological domains, and reproduce simultaneously both sets of experimental data. Importantly, this data deconvolution framework allows for structural heterogeneity between cells, and hence accounts for the expected plasticity of genome structures. As a case study we choose Drosophila melanogaster embryonic cells, for which both data types are available. Our three-dimensional genome structures have strong predictive power for structural features not directly visible in the initial data sets, and reproduce experimental hallmarks of the D. melanogaster genome organization from independent and our own imaging experiments. Also they reveal a number of new insights about genome organization and its functional relevance, including the preferred locations of heterochromatic satellites of different chromosomes, and observations about homologous pairing that cannot be directly observed in the original Hi-C or lamina-DamID data. Our approach allows systematic integration of Hi-C and lamina-DamID data for complete three-dimensional genome structure calculation, while also explicitly considering genome structural variability.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 106 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 106 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 30 28%
Researcher 25 24%
Student > Master 9 8%
Student > Bachelor 7 7%
Student > Doctoral Student 5 5%
Other 14 13%
Unknown 16 15%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 39 37%
Agricultural and Biological Sciences 22 21%
Physics and Astronomy 10 9%
Computer Science 4 4%
Neuroscience 2 2%
Other 11 10%
Unknown 18 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 27 December 2017.
All research outputs
#2,715,781
of 25,382,440 outputs
Outputs from Genome Biology
#2,119
of 4,468 outputs
Outputs of similar age
#49,084
of 326,986 outputs
Outputs of similar age from Genome Biology
#41
of 57 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,468 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has gotten more attention than average, scoring higher than 52% 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 326,986 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 84% of its contemporaries.
We're also able to compare this research output to 57 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.