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BioWord: A sequence manipulation suite for Microsoft Word

Overview of attention for article published in BMC Bioinformatics, January 2012
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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 (#15 of 5,885)
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

twitter
101 tweeters
wikipedia
1 Wikipedia page
googleplus
4 Google+ users
reddit
2 Redditors

Citations

dimensions_citation
9 Dimensions

Readers on

mendeley
222 Mendeley
citeulike
5 CiteULike
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Title
BioWord: A sequence manipulation suite for Microsoft Word
Published in
BMC Bioinformatics, January 2012
DOI 10.1186/1471-2105-13-124
Pubmed ID
Authors

Laura J Anzaldi, Daniel Muñoz-Fernández, Ivan Erill

Abstract

The ability to manipulate, edit and process DNA and protein sequences has rapidly become a necessary skill for practicing biologists across a wide swath of disciplines. In spite of this, most everyday sequence manipulation tools are distributed across several programs and web servers, sometimes requiring installation and typically involving frequent switching between applications. To address this problem, here we have developed BioWord, a macro-enabled self-installing template for Microsoft Word documents that integrates an extensive suite of DNA and protein sequence manipulation tools.

Twitter Demographics

The data shown below were collected from the profiles of 101 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 222 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 1%
Germany 2 <1%
United Kingdom 2 <1%
Sweden 2 <1%
Brazil 1 <1%
France 1 <1%
Netherlands 1 <1%
China 1 <1%
Russia 1 <1%
Other 1 <1%
Unknown 207 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 38 17%
Student > Ph. D. Student 17 8%
Student > Master 11 5%
Professor 8 4%
Other 8 4%
Other 26 12%
Unknown 114 51%
Readers by discipline Count As %
Agricultural and Biological Sciences 62 28%
Biochemistry, Genetics and Molecular Biology 11 5%
Computer Science 7 3%
Social Sciences 4 2%
Engineering 4 2%
Other 16 7%
Unknown 118 53%

Attention Score in Context

This research output has an Altmetric Attention Score of 73. 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 22 November 2020.
All research outputs
#320,292
of 16,273,071 outputs
Outputs from BMC Bioinformatics
#15
of 5,885 outputs
Outputs of similar age
#1,796
of 128,497 outputs
Outputs of similar age from BMC Bioinformatics
#1
of 6 outputs
Altmetric has tracked 16,273,071 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 5,885 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. 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 128,497 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 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them