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Alignment-free sequence comparison: benefits, applications, and tools

Overview of attention for article published in Genome Biology, October 2017
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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 (96th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

twitter
138 X users
patent
1 patent
facebook
2 Facebook pages
wikipedia
2 Wikipedia pages
googleplus
1 Google+ user

Citations

dimensions_citation
406 Dimensions

Readers on

mendeley
636 Mendeley
citeulike
1 CiteULike
Title
Alignment-free sequence comparison: benefits, applications, and tools
Published in
Genome Biology, October 2017
DOI 10.1186/s13059-017-1319-7
Pubmed ID
Authors

Andrzej Zielezinski, Susana Vinga, Jonas Almeida, Wojciech M. Karlowski

Abstract

Alignment-free sequence analyses have been applied to problems ranging from whole-genome phylogeny to the classification of protein families, identification of horizontally transferred genes, and detection of recombined sequences. The strength of these methods makes them particularly useful for next-generation sequencing data processing and analysis. However, many researchers are unclear about how these methods work, how they compare to alignment-based methods, and what their potential is for use for their research. We address these questions and provide a guide to the currently available alignment-free sequence analysis tools.

X Demographics

X Demographics

The data shown below were collected from the profiles of 138 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 636 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 636 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 129 20%
Researcher 105 17%
Student > Master 88 14%
Student > Bachelor 81 13%
Other 25 4%
Other 83 13%
Unknown 125 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 193 30%
Agricultural and Biological Sciences 131 21%
Computer Science 76 12%
Immunology and Microbiology 19 3%
Engineering 14 2%
Other 58 9%
Unknown 145 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 83. 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 05 September 2023.
All research outputs
#527,363
of 25,845,895 outputs
Outputs from Genome Biology
#297
of 4,524 outputs
Outputs of similar age
#11,044
of 332,902 outputs
Outputs of similar age from Genome Biology
#7
of 63 outputs
Altmetric has tracked 25,845,895 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,524 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.3. This one has done particularly well, scoring higher than 93% 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 332,902 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 96% of its contemporaries.
We're also able to compare this research output to 63 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.