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Effective machine-learning assembly for next-generation amplicon sequencing with very low coverage

Overview of attention for article published in BMC Bioinformatics, December 2019
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (52nd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
6 tweeters

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
12 Mendeley
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Title
Effective machine-learning assembly for next-generation amplicon sequencing with very low coverage
Published in
BMC Bioinformatics, December 2019
DOI 10.1186/s12859-019-3287-2
Pubmed ID
Authors

Louis Ranjard, Thomas K. F. Wong, Allen G. Rodrigo

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

Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 58%
Student > Bachelor 1 8%
Student > Master 1 8%
Unknown 3 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 25%
Agricultural and Biological Sciences 2 17%
Computer Science 1 8%
Nursing and Health Professions 1 8%
Unknown 5 42%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 13 December 2019.
All research outputs
#8,384,533
of 15,226,794 outputs
Outputs from BMC Bioinformatics
#3,075
of 5,584 outputs
Outputs of similar age
#159,427
of 345,336 outputs
Outputs of similar age from BMC Bioinformatics
#311
of 591 outputs
Altmetric has tracked 15,226,794 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,584 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.0. This one is in the 41st percentile – i.e., 41% of its peers scored the same or lower than it.
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 345,336 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.
We're also able to compare this research output to 591 others from the same source and published within six weeks on either side of this one. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.