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Extracting quantitative genetic interaction phenotypes from matrix combinatorial RNAi

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

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)

Mentioned by

blogs
1 blog
twitter
2 tweeters

Citations

dimensions_citation
14 Dimensions

Readers on

mendeley
56 Mendeley
citeulike
5 CiteULike
connotea
1 Connotea
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Title
Extracting quantitative genetic interaction phenotypes from matrix combinatorial RNAi
Published in
BMC Bioinformatics, August 2011
DOI 10.1186/1471-2105-12-342
Pubmed ID
Authors

Elin Axelsson, Thomas Sandmann, Thomas Horn, Michael Boutros, Wolfgang Huber, Bernd Fischer

Abstract

Systematic measurement of genetic interactions by combinatorial RNAi (co-RNAi) is a powerful tool for mapping functional modules and discovering components. It also provides insights into the role of epistasis on the way from genotype to phenotype. The interpretation of co-RNAi data requires computational and statistical analysis in order to detect interactions reliably and sensitively.

Twitter Demographics

The data shown below were collected from the profiles of 2 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 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 5 9%
United Kingdom 1 2%
United States 1 2%
Luxembourg 1 2%
Unknown 48 86%

Demographic breakdown

Readers by professional status Count As %
Researcher 24 43%
Student > Ph. D. Student 14 25%
Student > Doctoral Student 3 5%
Student > Master 3 5%
Professor 3 5%
Other 5 9%
Unknown 4 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 31 55%
Biochemistry, Genetics and Molecular Biology 10 18%
Computer Science 5 9%
Mathematics 2 4%
Business, Management and Accounting 1 2%
Other 2 4%
Unknown 5 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 23 August 2011.
All research outputs
#2,124,362
of 13,779,248 outputs
Outputs from BMC Bioinformatics
#915
of 5,132 outputs
Outputs of similar age
#14,755
of 91,188 outputs
Outputs of similar age from BMC Bioinformatics
#1
of 1 outputs
Altmetric has tracked 13,779,248 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,132 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done well, scoring higher than 82% 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 91,188 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 83% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them