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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 (93rd percentile)

Mentioned by

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

Citations

dimensions_citation
5465 Dimensions

Readers on

mendeley
3709 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 6 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 3,709 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 54 1%
Germany 32 <1%
United Kingdom 23 <1%
Brazil 22 <1%
France 15 <1%
Spain 14 <1%
Mexico 9 <1%
Australia 8 <1%
Denmark 8 <1%
Other 86 2%
Unknown 3438 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1026 28%
Researcher 727 20%
Student > Master 545 15%
Student > Bachelor 409 11%
Student > Doctoral Student 203 5%
Other 509 14%
Unknown 290 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 1823 49%
Biochemistry, Genetics and Molecular Biology 817 22%
Computer Science 140 4%
Immunology and Microbiology 110 3%
Environmental Science 96 3%
Other 319 9%
Unknown 404 11%

Attention Score in Context

This research output has an Altmetric Attention Score of 18. 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 March 2019.
All research outputs
#876,051
of 13,483,547 outputs
Outputs from BMC Bioinformatics
#244
of 5,040 outputs
Outputs of similar age
#5,703
of 86,778 outputs
Outputs of similar age from BMC Bioinformatics
#1
of 1 outputs
Altmetric has tracked 13,483,547 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 5,040 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done particularly well, scoring higher than 95% 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 86,778 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