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Phenotype forecasting with SNPs data through gene-based Bayesian networks

Overview of attention for article published in BMC Bioinformatics, January 2009
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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 (76th percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

Mentioned by

patent
3 patents

Citations

dimensions_citation
10 Dimensions

Readers on

mendeley
41 Mendeley
citeulike
2 CiteULike
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Title
Phenotype forecasting with SNPs data through gene-based Bayesian networks
Published in
BMC Bioinformatics, January 2009
DOI 10.1186/1471-2105-10-s2-s7
Pubmed ID
Authors

Alberto Malovini, Angelo Nuzzo, Fulvia Ferrazzi, Annibale A Puca, Riccardo Bellazzi

Mendeley readers

The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Philippines 1 2%
Portugal 1 2%
Germany 1 2%
Unknown 37 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 17%
Researcher 6 15%
Professor 3 7%
Student > Master 2 5%
Lecturer > Senior Lecturer 1 2%
Other 4 10%
Unknown 18 44%
Readers by discipline Count As %
Agricultural and Biological Sciences 11 27%
Computer Science 7 17%
Medicine and Dentistry 3 7%
Engineering 1 2%
Unknown 19 46%

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 13 August 2015.
All research outputs
#1,642,200
of 9,597,649 outputs
Outputs from BMC Bioinformatics
#902
of 4,086 outputs
Outputs of similar age
#24,526
of 103,627 outputs
Outputs of similar age from BMC Bioinformatics
#12
of 41 outputs
Altmetric has tracked 9,597,649 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,086 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.0. This one has done well, scoring higher than 77% 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 103,627 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 76% of its contemporaries.
We're also able to compare this research output to 41 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.