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Developing reproducible bioinformatics analysis workflows for heterogeneous computing environments to support African genomics

Overview of attention for article published in BMC Bioinformatics, November 2018
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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 (94th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

twitter
67 X users

Citations

dimensions_citation
32 Dimensions

Readers on

mendeley
145 Mendeley
citeulike
1 CiteULike
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Title
Developing reproducible bioinformatics analysis workflows for heterogeneous computing environments to support African genomics
Published in
BMC Bioinformatics, November 2018
DOI 10.1186/s12859-018-2446-1
Pubmed ID
Authors

Shakuntala Baichoo, Yassine Souilmi, Sumir Panji, Gerrit Botha, Ayton Meintjes, Scott Hazelhurst, Hocine Bendou, Eugene de Beste, Phelelani T. Mpangase, Oussema Souiai, Mustafa Alghali, Long Yi, Brian D. O’Connor, Michael Crusoe, Don Armstrong, Shaun Aron, Fourie Joubert, Azza E. Ahmed, Mamana Mbiyavanga, Peter van Heusden, Lerato E. Magosi, Jennie Zermeno, Liudmila Sergeevna Mainzer, Faisal M. Fadlelmola, C. Victor Jongeneel, Nicola Mulder

X Demographics

X Demographics

The data shown below were collected from the profiles of 67 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 145 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 145 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 24 17%
Student > Master 18 12%
Researcher 17 12%
Student > Bachelor 14 10%
Other 7 5%
Other 21 14%
Unknown 44 30%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 41 28%
Agricultural and Biological Sciences 21 14%
Computer Science 13 9%
Medicine and Dentistry 7 5%
Engineering 4 3%
Other 12 8%
Unknown 47 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 41. 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 June 2020.
All research outputs
#1,000,005
of 25,299,129 outputs
Outputs from BMC Bioinformatics
#76
of 7,672 outputs
Outputs of similar age
#22,621
of 451,044 outputs
Outputs of similar age from BMC Bioinformatics
#2
of 190 outputs
Altmetric has tracked 25,299,129 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,672 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done particularly well, scoring higher than 99% 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 451,044 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 94% of its contemporaries.
We're also able to compare this research output to 190 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 99% of its contemporaries.