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X Demographics
Mendeley readers
Attention Score in Context
| Title |
RNA-seq analysis identifies an intricate regulatory network controlling cluster root development in white lupin
|
|---|---|
| Published in |
BMC Genomics, March 2014
|
| DOI | 10.1186/1471-2164-15-230 |
| Pubmed ID | |
| Authors |
David Secco, Huixia Shou, James Whelan, Oliver Berkowitz |
| Abstract |
Highly adapted plant species are able to alter their root architecture to improve nutrient uptake and thrive in environments with limited nutrient supply. Cluster roots (CRs) are specialised structures of dense lateral roots formed by several plant species for the effective mining of nutrient rich soil patches through a combination of increased surface area and exudation of carboxylates. White lupin is becoming a model-species allowing for the discovery of gene networks involved in CR development. A greater understanding of the underlying molecular mechanisms driving these developmental processes is important for the generation of smarter plants for a world with diminishing resources to improve food security. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 2% |
| Switzerland | 1 | 2% |
| Unknown | 61 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 15 | 24% |
| Researcher | 11 | 17% |
| Student > Master | 7 | 11% |
| Student > Doctoral Student | 7 | 11% |
| Professor | 4 | 6% |
| Other | 11 | 17% |
| Unknown | 8 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 40 | 63% |
| Biochemistry, Genetics and Molecular Biology | 10 | 16% |
| Medicine and Dentistry | 2 | 3% |
| Computer Science | 1 | 2% |
| Nursing and Health Professions | 1 | 2% |
| Other | 0 | 0% |
| Unknown | 9 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 29 March 2014.
All research outputs
#18,137,447
of 23,301,510 outputs
Outputs from BMC Genomics
#7,632
of 10,742 outputs
Outputs of similar age
#156,408
of 225,586 outputs
Outputs of similar age from BMC Genomics
#94
of 158 outputs
Altmetric has tracked 23,301,510 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,742 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 23rd percentile – i.e., 23% of its peers scored the same or lower than it.
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 225,586 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 158 others from the same source and published within six weeks on either side of this one. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.