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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

  • Above-average Attention Score compared to outputs of the same age (64th percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

Mentioned by

twitter
7 tweeters

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
29 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 7 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 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 29 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 7 24%
Unspecified 2 7%
Student > Bachelor 2 7%
Student > Ph. D. Student 2 7%
Other 1 3%
Other 4 14%
Unknown 11 38%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 28%
Agricultural and Biological Sciences 4 14%
Unspecified 2 7%
Medicine and Dentistry 2 7%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Other 2 7%
Unknown 10 34%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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
#6,175,360
of 22,034,959 outputs
Outputs from BMC Bioinformatics
#2,421
of 7,083 outputs
Outputs of similar age
#99,284
of 283,294 outputs
Outputs of similar age from BMC Bioinformatics
#9
of 27 outputs
Altmetric has tracked 22,034,959 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 7,083 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 64% 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 283,294 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 64% 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 gotten more attention than average, scoring higher than 70% of its contemporaries.