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Ten recommendations for creating usable bioinformatics command line software

Overview of attention for article published in Giga Science, November 2013
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#12 of 740)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

blogs
2 blogs
twitter
236 tweeters
peer_reviews
1 peer review site
facebook
1 Facebook page
googleplus
3 Google+ users

Citations

dimensions_citation
29 Dimensions

Readers on

mendeley
159 Mendeley
citeulike
4 CiteULike
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Title
Ten recommendations for creating usable bioinformatics command line software
Published in
Giga Science, November 2013
DOI 10.1186/2047-217x-2-15
Pubmed ID
Authors

Torsten Seemann

Abstract

Bioinformatics software varies greatly in quality. In terms of usability, the command line interface is the first experience a user will have of a tool. Unfortunately, this is often also the last time a tool will be used. Here I present ten recommendations for command line software author's tools to follow, which I believe would greatly improve the uptake and usability of their products, waste less user's time, and improve the quality of scientific analyses.

Twitter Demographics

The data shown below were collected from the profiles of 236 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 159 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 3%
United Kingdom 4 3%
Spain 3 2%
Netherlands 2 1%
Hong Kong 2 1%
Sweden 2 1%
Canada 1 <1%
Norway 1 <1%
Mexico 1 <1%
Other 7 4%
Unknown 131 82%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 43 27%
Researcher 41 26%
Student > Master 17 11%
Student > Bachelor 14 9%
Other 12 8%
Other 25 16%
Unknown 7 4%
Readers by discipline Count As %
Agricultural and Biological Sciences 80 50%
Biochemistry, Genetics and Molecular Biology 29 18%
Computer Science 18 11%
Medicine and Dentistry 4 3%
Immunology and Microbiology 3 2%
Other 15 9%
Unknown 10 6%

Attention Score in Context

This research output has an Altmetric Attention Score of 157. 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 01 May 2020.
All research outputs
#117,087
of 15,387,755 outputs
Outputs from Giga Science
#12
of 740 outputs
Outputs of similar age
#1,415
of 187,368 outputs
Outputs of similar age from Giga Science
#2
of 17 outputs
Altmetric has tracked 15,387,755 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 740 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 22.9. This one has done particularly well, scoring higher than 98% 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 187,368 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 99% of its contemporaries.
We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.