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Readjoiner: a fast and memory efficient string graph-based sequence assembler

Overview of attention for article published in BMC Bioinformatics, May 2012
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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 (91st percentile)

Mentioned by

blogs
1 blog
twitter
17 X users

Citations

dimensions_citation
54 Dimensions

Readers on

mendeley
120 Mendeley
citeulike
11 CiteULike
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Title
Readjoiner: a fast and memory efficient string graph-based sequence assembler
Published in
BMC Bioinformatics, May 2012
DOI 10.1186/1471-2105-13-82
Pubmed ID
Authors

Giorgio Gonnella, Stefan Kurtz

Abstract

Ongoing improvements in throughput of the next-generation sequencing technologies challenge the current generation of de novo sequence assemblers. Most recent sequence assemblers are based on the construction of a de Bruijn graph. An alternative framework of growing interest is the assembly string graph, not necessitating a division of the reads into k-mers, but requiring fast algorithms for the computation of suffix-prefix matches among all pairs of reads.

X Demographics

X Demographics

The data shown below were collected from the profiles of 17 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 120 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 5%
Sweden 2 2%
Germany 1 <1%
Italy 1 <1%
Netherlands 1 <1%
Colombia 1 <1%
United Kingdom 1 <1%
New Zealand 1 <1%
Taiwan 1 <1%
Other 5 4%
Unknown 100 83%

Demographic breakdown

Readers by professional status Count As %
Researcher 36 30%
Student > Ph. D. Student 27 23%
Student > Master 13 11%
Other 10 8%
Student > Doctoral Student 10 8%
Other 19 16%
Unknown 5 4%
Readers by discipline Count As %
Agricultural and Biological Sciences 54 45%
Computer Science 36 30%
Biochemistry, Genetics and Molecular Biology 13 11%
Mathematics 2 2%
Linguistics 1 <1%
Other 4 3%
Unknown 10 8%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 21. 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 07 February 2015.
All research outputs
#1,746,149
of 25,161,628 outputs
Outputs from BMC Bioinformatics
#315
of 7,656 outputs
Outputs of similar age
#9,899
of 168,980 outputs
Outputs of similar age from BMC Bioinformatics
#9
of 98 outputs
Altmetric has tracked 25,161,628 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 7,656 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. 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 168,980 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 98 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 91% of its contemporaries.