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Extending reference assembly models

Overview of attention for article published in Genome Biology, January 2015
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

blogs
4 blogs
twitter
90 X users
patent
1 patent
facebook
2 Facebook pages
googleplus
1 Google+ user

Citations

dimensions_citation
144 Dimensions

Readers on

mendeley
270 Mendeley
citeulike
8 CiteULike
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Title
Extending reference assembly models
Published in
Genome Biology, January 2015
DOI 10.1186/s13059-015-0587-3
Pubmed ID
Authors

Deanna M Church, Valerie A Schneider, Karyn Meltz Steinberg, Michael C Schatz, Aaron R Quinlan, Chen-Shan Chin, Paul A Kitts, Bronwen Aken, Gabor T Marth, Michael M Hoffman, Javier Herrero, M Lisandra Zepeda Mendoza, Richard Durbin, Paul Flicek

Abstract

The human genome reference assembly is crucial for aligning and analyzing sequence data, and for genome annotation, among other roles. However, the models and analysis assumptions that underlie the current assembly need revising to fully represent human sequence diversity. Improved analysis tools and updated data reporting formats are also required.

X Demographics

X Demographics

The data shown below were collected from the profiles of 90 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 270 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 10 4%
Germany 3 1%
France 2 <1%
Norway 2 <1%
Netherlands 2 <1%
United Kingdom 2 <1%
Italy 2 <1%
Brazil 1 <1%
Canada 1 <1%
Other 4 1%
Unknown 241 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 65 24%
Student > Ph. D. Student 62 23%
Student > Master 34 13%
Other 21 8%
Student > Bachelor 19 7%
Other 32 12%
Unknown 37 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 95 35%
Biochemistry, Genetics and Molecular Biology 71 26%
Computer Science 29 11%
Medicine and Dentistry 11 4%
Mathematics 5 2%
Other 11 4%
Unknown 48 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 78. 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 22 February 2024.
All research outputs
#545,938
of 25,374,917 outputs
Outputs from Genome Biology
#317
of 4,467 outputs
Outputs of similar age
#6,840
of 359,728 outputs
Outputs of similar age from Genome Biology
#7
of 70 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% 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 has done particularly well, scoring higher than 92% 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 359,728 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 70 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.