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The real cost of sequencing: scaling computation to keep pace with data generation

Overview of attention for article published in Genome Biology, March 2016
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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 (97th percentile)

Mentioned by

blogs
4 blogs
twitter
192 X users
facebook
4 Facebook pages

Citations

dimensions_citation
305 Dimensions

Readers on

mendeley
645 Mendeley
citeulike
6 CiteULike
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Title
The real cost of sequencing: scaling computation to keep pace with data generation
Published in
Genome Biology, March 2016
DOI 10.1186/s13059-016-0917-0
Pubmed ID
Authors

Paul Muir, Shantao Li, Shaoke Lou, Daifeng Wang, Daniel J Spakowicz, Leonidas Salichos, Jing Zhang, George M. Weinstock, Farren Isaacs, Joel Rozowsky, Mark Gerstein

Abstract

As the cost of sequencing continues to decrease and the amount of sequence data generated grows, new paradigms for data storage and analysis are increasingly important. The relative scaling behavior of these evolving technologies will impact genomics research moving forward.

X Demographics

X Demographics

The data shown below were collected from the profiles of 192 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 645 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 6 <1%
United States 6 <1%
United Kingdom 5 <1%
Netherlands 4 <1%
Brazil 4 <1%
France 3 <1%
Italy 2 <1%
Norway 1 <1%
Austria 1 <1%
Other 12 2%
Unknown 601 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 155 24%
Researcher 148 23%
Student > Master 76 12%
Student > Bachelor 65 10%
Student > Doctoral Student 25 4%
Other 85 13%
Unknown 91 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 228 35%
Biochemistry, Genetics and Molecular Biology 147 23%
Computer Science 51 8%
Medicine and Dentistry 26 4%
Environmental Science 15 2%
Other 68 11%
Unknown 110 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 134. 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 07 July 2022.
All research outputs
#315,091
of 25,706,302 outputs
Outputs from Genome Biology
#132
of 4,504 outputs
Outputs of similar age
#5,641
of 315,645 outputs
Outputs of similar age from Genome Biology
#2
of 73 outputs
Altmetric has tracked 25,706,302 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,504 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 97% 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 315,645 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 73 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 97% of its contemporaries.