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RAFTS3G: an efficient and versatile clustering software to analyses in large protein datasets

Overview of attention for article published in BMC Bioinformatics, July 2019
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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 (70th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

twitter
9 tweeters

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
23 Mendeley
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Title
RAFTS3G: an efficient and versatile clustering software to analyses in large protein datasets
Published in
BMC Bioinformatics, July 2019
DOI 10.1186/s12859-019-2973-4
Pubmed ID
Authors

Bruno Thiago de Lima Nichio, Aryel Marlus Repula de Oliveira, Camilla Reginatto de Pierri, Leticia Graziela Costa Santos, Alexandre Quadros Lejambre, Ricardo Assunção Vialle, Nilson Antônio da Rocha Coimbra, Dieval Guizelini, Jeroniza Nunes Marchaukoski, Fabio de Oliveira Pedrosa, Roberto Tadeu Raittz

Twitter Demographics

The data shown below were collected from the profiles of 9 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 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 26%
Student > Bachelor 2 9%
Other 1 4%
Student > Doctoral Student 1 4%
Student > Ph. D. Student 1 4%
Other 3 13%
Unknown 9 39%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 35%
Agricultural and Biological Sciences 3 13%
Medicine and Dentistry 2 9%
Computer Science 1 4%
Engineering 1 4%
Other 0 0%
Unknown 8 35%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 02 August 2019.
All research outputs
#4,991,691
of 20,655,167 outputs
Outputs from BMC Bioinformatics
#1,881
of 6,819 outputs
Outputs of similar age
#81,829
of 279,385 outputs
Outputs of similar age from BMC Bioinformatics
#7
of 27 outputs
Altmetric has tracked 20,655,167 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,819 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 71% 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 279,385 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 70% of its contemporaries.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.