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The Ruby UCSC API: accessing the UCSC genome database using Ruby

Overview of attention for article published in BMC Bioinformatics, September 2012
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

twitter
16 tweeters

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
21 Mendeley
citeulike
2 CiteULike
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Title
The Ruby UCSC API: accessing the UCSC genome database using Ruby
Published in
BMC Bioinformatics, September 2012
DOI 10.1186/1471-2105-13-240
Pubmed ID
Authors

Hiroyuki Mishima, Jan Aerts, Toshiaki Katayama, Raoul J P Bonnal, Koh-ichiro Yoshiura

Abstract

The University of California, Santa Cruz (UCSC) genome database is among the most used sources of genomic annotation in human and other organisms. The database offers an excellent web-based graphical user interface (the UCSC genome browser) and several means for programmatic queries. A simple application programming interface (API) in a scripting language aimed at the biologist was however not yet available. Here, we present the Ruby UCSC API, a library to access the UCSC genome database using Ruby.

Twitter Demographics

The data shown below were collected from the profiles of 16 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 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 4 19%
Spain 1 5%
Belgium 1 5%
Unknown 15 71%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 29%
Student > Ph. D. Student 4 19%
Student > Bachelor 4 19%
Professor > Associate Professor 3 14%
Professor 2 10%
Other 2 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 43%
Computer Science 4 19%
Biochemistry, Genetics and Molecular Biology 2 10%
Medicine and Dentistry 2 10%
Engineering 2 10%
Other 1 5%
Unknown 1 5%

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 12 November 2012.
All research outputs
#1,273,266
of 12,732,596 outputs
Outputs from BMC Bioinformatics
#501
of 4,738 outputs
Outputs of similar age
#12,829
of 127,955 outputs
Outputs of similar age from BMC Bioinformatics
#1
of 11 outputs
Altmetric has tracked 12,732,596 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,738 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done well, scoring higher than 89% 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 127,955 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 11 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.