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NCBI BLAST+ integrated into Galaxy

Overview of attention for article published in Giga Science, August 2015
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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 (93rd percentile)

Mentioned by

1 blog
28 tweeters
1 peer review site
1 Facebook page
2 Google+ users


62 Dimensions

Readers on

116 Mendeley
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NCBI BLAST+ integrated into Galaxy
Published in
Giga Science, August 2015
DOI 10.1186/s13742-015-0080-7
Pubmed ID

Peter J. A. Cock, John M. Chilton, Björn Grüning, James E. Johnson, Nicola Soranzo


The NCBI BLAST suite has become ubiquitous in modern molecular biology and is used for small tasks such as checking capillary sequencing results of single PCR products, genome annotation or even larger scale pan-genome analyses. For early adopters of the Galaxy web-based biomedical data analysis platform, integrating BLAST into Galaxy was a natural step for sequence comparison workflows. The command line NCBI BLAST+ tool suite was wrapped for use within Galaxy. Appropriate datatypes were defined as needed. The integration of the BLAST+ tool suite into Galaxy has the goal of making common BLAST tasks easy and advanced tasks possible. This project is an informal international collaborative effort, and is deployed and used on Galaxy servers worldwide. Several examples of applications are described here.

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 116 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
China 2 2%
Canada 1 <1%
Brazil 1 <1%
Netherlands 1 <1%
Spain 1 <1%
Germany 1 <1%
Unknown 107 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 22 19%
Student > Ph. D. Student 21 18%
Student > Master 18 16%
Student > Bachelor 17 15%
Student > Doctoral Student 12 10%
Other 16 14%
Unknown 10 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 40 34%
Biochemistry, Genetics and Molecular Biology 34 29%
Computer Science 10 9%
Immunology and Microbiology 5 4%
Engineering 4 3%
Other 8 7%
Unknown 15 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 27. 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 28 December 2019.
All research outputs
of 15,329,269 outputs
Outputs from Giga Science
of 740 outputs
Outputs of similar age
of 240,881 outputs
Outputs of similar age from Giga Science
of 1 outputs
Altmetric has tracked 15,329,269 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th 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 23.3. This one has done well, scoring higher than 75% 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 240,881 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 93% of its contemporaries.
We're also able to compare this research output to 1 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