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BLAST+: architecture and applications

Overview of attention for article published in BMC Bioinformatics, January 2009
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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)

Mentioned by

policy
1 policy source
twitter
7 tweeters
patent
4 patents
facebook
1 Facebook page
wikipedia
1 Wikipedia page
q&a
2 Q&A threads

Citations

dimensions_citation
6945 Dimensions

Readers on

mendeley
4427 Mendeley
citeulike
52 CiteULike
connotea
5 Connotea
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Title
BLAST+: architecture and applications
Published in
BMC Bioinformatics, January 2009
DOI 10.1186/1471-2105-10-421
Pubmed ID
Authors

Christiam Camacho, George Coulouris, Vahram Avagyan, Ning Ma, Jason Papadopoulos, Kevin Bealer, Thomas L Madden

Abstract

Sequence similarity searching is a very important bioinformatics task. While Basic Local Alignment Search Tool (BLAST) outperforms exact methods through its use of heuristics, the speed of the current BLAST software is suboptimal for very long queries or database sequences. There are also some shortcomings in the user-interface of the current command-line applications.

Twitter Demographics

The data shown below were collected from the profiles of 7 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 4,427 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 51 1%
Germany 32 <1%
United Kingdom 23 <1%
Brazil 21 <1%
France 15 <1%
Spain 14 <1%
Mexico 9 <1%
Australia 8 <1%
Denmark 8 <1%
Other 83 2%
Unknown 4163 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1166 26%
Researcher 816 18%
Student > Master 645 15%
Student > Bachelor 512 12%
Student > Doctoral Student 251 6%
Other 602 14%
Unknown 435 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 1962 44%
Biochemistry, Genetics and Molecular Biology 1057 24%
Computer Science 154 3%
Immunology and Microbiology 135 3%
Environmental Science 122 3%
Other 422 10%
Unknown 575 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 22. 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 02 September 2020.
All research outputs
#990,669
of 16,311,897 outputs
Outputs from BMC Bioinformatics
#196
of 5,894 outputs
Outputs of similar age
#5,304
of 94,513 outputs
Outputs of similar age from BMC Bioinformatics
#1
of 1 outputs
Altmetric has tracked 16,311,897 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,894 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 96% 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 94,513 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 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