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GiA Roots: software for the high throughput analysis of plant root system architecture

Overview of attention for article published in BMC Plant Biology, January 2012
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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 (87th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

blogs
1 blog
twitter
3 tweeters

Citations

dimensions_citation
155 Dimensions

Readers on

mendeley
288 Mendeley
citeulike
2 CiteULike
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Title
GiA Roots: software for the high throughput analysis of plant root system architecture
Published in
BMC Plant Biology, January 2012
DOI 10.1186/1471-2229-12-116
Pubmed ID
Authors

Taras Galkovskyi, Yuriy Mileyko, Alexander Bucksch, Brad Moore, Olga Symonova, Charles A Price, Christopher N Topp, Anjali S Iyer-Pascuzzi, Paul R Zurek, Suqin Fang, John Harer, Philip N Benfey, Joshua S Weitz

Abstract

Characterizing root system architecture (RSA) is essential to understanding the development and function of vascular plants. Identifying RSA-associated genes also represents an underexplored opportunity for crop improvement. Software tools are needed to accelerate the pace at which quantitative traits of RSA are estimated from images of root networks.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 288 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 7 2%
Spain 3 1%
Chile 2 <1%
United Kingdom 2 <1%
Brazil 2 <1%
India 1 <1%
Finland 1 <1%
Australia 1 <1%
Argentina 1 <1%
Other 4 1%
Unknown 264 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 81 28%
Researcher 53 18%
Student > Master 43 15%
Student > Bachelor 23 8%
Student > Doctoral Student 17 6%
Other 44 15%
Unknown 27 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 177 61%
Biochemistry, Genetics and Molecular Biology 22 8%
Environmental Science 16 6%
Engineering 13 5%
Computer Science 9 3%
Other 13 5%
Unknown 38 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 14 August 2012.
All research outputs
#1,622,997
of 12,410,450 outputs
Outputs from BMC Plant Biology
#98
of 1,566 outputs
Outputs of similar age
#15,419
of 120,952 outputs
Outputs of similar age from BMC Plant Biology
#4
of 16 outputs
Altmetric has tracked 12,410,450 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,566 research outputs from this source. They receive a mean Attention Score of 3.2. This one has done particularly well, scoring higher than 93% 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 120,952 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 87% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.