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MIR@NT@N: a framework integrating transcription factors, microRNAs and their targets to identify sub-network motifs in a meta-regulation network model

Overview of attention for article published in BMC Bioinformatics, January 2011
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (62nd percentile)
  • Good Attention Score compared to outputs of the same age and source (67th percentile)

Mentioned by

patent
1 patent

Citations

dimensions_citation
56 Dimensions

Readers on

mendeley
103 Mendeley
citeulike
4 CiteULike
connotea
1 Connotea
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Title
MIR@NT@N: a framework integrating transcription factors, microRNAs and their targets to identify sub-network motifs in a meta-regulation network model
Published in
BMC Bioinformatics, January 2011
DOI 10.1186/1471-2105-12-67
Pubmed ID
Authors

Antony Le Béchec, Elodie Portales-Casamar, Guillaume Vetter, Michèle Moes, Pierre-Joachim Zindy, Anne Saumet, David Arenillas, Charles Theillet, Wyeth W Wasserman, Charles-Henri Lecellier, Evelyne Friederich

Mendeley readers

The data shown below were compiled from readership statistics for 103 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 3 3%
France 3 3%
Brazil 3 3%
India 3 3%
United Kingdom 3 3%
United States 2 2%
Belgium 2 2%
Mexico 1 <1%
Norway 1 <1%
Other 4 4%
Unknown 78 76%

Demographic breakdown

Readers by professional status Count As %
Researcher 36 35%
Student > Ph. D. Student 30 29%
Professor > Associate Professor 9 9%
Student > Master 8 8%
Student > Postgraduate 5 5%
Other 14 14%
Unknown 1 <1%
Readers by discipline Count As %
Agricultural and Biological Sciences 68 66%
Computer Science 10 10%
Medicine and Dentistry 7 7%
Biochemistry, Genetics and Molecular Biology 7 7%
Engineering 3 3%
Other 5 5%
Unknown 3 3%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 26 October 2017.
All research outputs
#3,434,529
of 12,050,803 outputs
Outputs from BMC Bioinformatics
#1,654
of 4,381 outputs
Outputs of similar age
#98,148
of 265,741 outputs
Outputs of similar age from BMC Bioinformatics
#27
of 90 outputs
Altmetric has tracked 12,050,803 research outputs across all sources so far. This one is in the 49th percentile – i.e., 49% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,381 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 52% 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 265,741 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 62% of its contemporaries.
We're also able to compare this research output to 90 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 67% of its contemporaries.