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A computational method to predict topologically associating domain boundaries combining histone Marks and sequence information

Overview of attention for article published in BMC Genomics, December 2019
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (73rd percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

twitter
13 tweeters

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
24 Mendeley
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Title
A computational method to predict topologically associating domain boundaries combining histone Marks and sequence information
Published in
BMC Genomics, December 2019
DOI 10.1186/s12864-019-6303-z
Pubmed ID
Authors

Wei Gan, Juan Luo, Yi Zhou Li, Jia Li Guo, Min Zhu, Meng Long Li

Twitter Demographics

The data shown below were collected from the profiles of 13 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 25%
Student > Ph. D. Student 4 17%
Professor 2 8%
Other 2 8%
Student > Master 2 8%
Other 2 8%
Unknown 6 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 9 38%
Agricultural and Biological Sciences 3 13%
Computer Science 2 8%
Arts and Humanities 1 4%
Environmental Science 1 4%
Other 2 8%
Unknown 6 25%

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 08 January 2020.
All research outputs
#3,208,497
of 16,568,277 outputs
Outputs from BMC Genomics
#1,536
of 9,075 outputs
Outputs of similar age
#102,442
of 383,977 outputs
Outputs of similar age from BMC Genomics
#131
of 819 outputs
Altmetric has tracked 16,568,277 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,075 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done well, scoring higher than 83% 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 383,977 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 73% of its contemporaries.
We're also able to compare this research output to 819 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.