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Achieving large and distant ancestral genome inference by using an improved discrete quantum-behaved particle swarm optimization algorithm

Overview of attention for article published in BMC Bioinformatics, November 2020
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (78th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

blogs
1 blog
twitter
6 tweeters

Readers on

mendeley
2 Mendeley
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Title
Achieving large and distant ancestral genome inference by using an improved discrete quantum-behaved particle swarm optimization algorithm
Published in
BMC Bioinformatics, November 2020
DOI 10.1186/s12859-020-03833-7
Pubmed ID
Authors

Zhaojuan Zhang, Wanliang Wang, Ruofan Xia, Gaofeng Pan, Jiandong Wang, Jijun Tang

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

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 1 50%
Researcher 1 50%
Readers by discipline Count As %
Computer Science 1 50%
Agricultural and Biological Sciences 1 50%

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 01 December 2020.
All research outputs
#2,671,522
of 19,539,469 outputs
Outputs from BMC Bioinformatics
#1,036
of 6,619 outputs
Outputs of similar age
#83,760
of 389,071 outputs
Outputs of similar age from BMC Bioinformatics
#94
of 484 outputs
Altmetric has tracked 19,539,469 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,619 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has done well, scoring higher than 84% 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 389,071 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 78% of its contemporaries.
We're also able to compare this research output to 484 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.