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Using next generation transcriptome sequencing to predict an ectomycorrhizal metabolome

Overview of attention for article published in BMC Systems Biology, May 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 (74th percentile)

Mentioned by

twitter
6 X users

Citations

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64 Dimensions

Readers on

mendeley
133 Mendeley
citeulike
1 CiteULike
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Title
Using next generation transcriptome sequencing to predict an ectomycorrhizal metabolome
Published in
BMC Systems Biology, May 2011
DOI 10.1186/1752-0509-5-70
Pubmed ID
Authors

Peter E Larsen, Avinash Sreedasyam, Geetika Trivedi, Gopi K Podila, Leland J Cseke, Frank R Collart

Abstract

Mycorrhizae, symbiotic interactions between soil fungi and tree roots, are ubiquitous in terrestrial ecosystems. The fungi contribute phosphorous, nitrogen and mobilized nutrients from organic matter in the soil and in return the fungus receives photosynthetically-derived carbohydrates. This union of plant and fungal metabolisms is the mycorrhizal metabolome. Understanding this symbiotic relationship at a molecular level provides important contributions to the understanding of forest ecosystems and global carbon cycling.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 133 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 4%
Germany 2 2%
Brazil 2 2%
Mexico 2 2%
Japan 2 2%
Indonesia 1 <1%
United Kingdom 1 <1%
Sweden 1 <1%
Switzerland 1 <1%
Other 1 <1%
Unknown 115 86%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 37 28%
Researcher 35 26%
Student > Master 16 12%
Student > Doctoral Student 12 9%
Student > Bachelor 9 7%
Other 10 8%
Unknown 14 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 84 63%
Biochemistry, Genetics and Molecular Biology 12 9%
Environmental Science 8 6%
Computer Science 4 3%
Chemistry 3 2%
Other 8 6%
Unknown 14 11%
Attention Score in Context

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 09 October 2022.
All research outputs
#8,474,037
of 25,373,627 outputs
Outputs from BMC Systems Biology
#315
of 1,132 outputs
Outputs of similar age
#45,376
of 121,377 outputs
Outputs of similar age from BMC Systems Biology
#7
of 27 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
So far Altmetric has tracked 1,132 research outputs from this source. They receive a mean Attention Score of 3.7. 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 121,377 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 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 74% of its contemporaries.