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Processing genome scale tabular data with wormtable

Overview of attention for article published in BMC Bioinformatics, December 2013
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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 (94th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

blogs
1 blog
twitter
28 tweeters
facebook
1 Facebook page

Citations

dimensions_citation
11 Dimensions

Readers on

mendeley
31 Mendeley
citeulike
1 CiteULike
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Title
Processing genome scale tabular data with wormtable
Published in
BMC Bioinformatics, December 2013
DOI 10.1186/1471-2105-14-356
Pubmed ID
Authors

Jerome Kelleher, Rob W Ness, Daniel L Halligan

Abstract

Modern biological science generates a vast amount of data, the analysis of which presents a major challenge to researchers. Data are commonly represented in tables stored as plain text files and require line-by-line parsing for analysis, which is time consuming and error prone. Furthermore, there is no simple means of indexing these files so that rows containing particular values can be quickly found.

Twitter Demographics

The data shown below were collected from the profiles of 28 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 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 6%
Sweden 1 3%
Australia 1 3%
Russia 1 3%
Germany 1 3%
Unknown 25 81%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 29%
Student > Ph. D. Student 6 19%
Other 3 10%
Student > Master 3 10%
Student > Doctoral Student 2 6%
Other 7 23%
Unknown 1 3%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 55%
Biochemistry, Genetics and Molecular Biology 5 16%
Linguistics 2 6%
Computer Science 1 3%
Mathematics 1 3%
Other 3 10%
Unknown 2 6%

Attention Score in Context

This research output has an Altmetric Attention Score of 24. 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 04 March 2014.
All research outputs
#765,999
of 14,573,111 outputs
Outputs from BMC Bioinformatics
#146
of 5,420 outputs
Outputs of similar age
#13,527
of 255,771 outputs
Outputs of similar age from BMC Bioinformatics
#14
of 425 outputs
Altmetric has tracked 14,573,111 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,420 research outputs from this source. They receive a mean Attention Score of 4.9. 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 255,771 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 425 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 96% of its contemporaries.