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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Large-Scale Plant Ionomics
|
|---|---|
| Chapter number | 17 |
| Book title |
Plant Mineral Nutrients
|
| Published in |
Methods in molecular biology, October 2012
|
| DOI | 10.1007/978-1-62703-152-3_17 |
| Pubmed ID | |
| Book ISBNs |
978-1-62703-151-6, 978-1-62703-152-3
|
| Authors |
John M. C. Danku, Brett Lahner, Elena Yakubova, David E. Salt |
| Editors |
Frans J.M. Maathuis |
| Abstract |
Large-scale phenotyping methods are at the heart of efficiently deciphering the functions of genes and gene networks in the postgenomic era. In order to obtain meaningful results when comparing natural variants, and mutants and wild-types during large-scale quantitative analyses, necessary precautions must be employed throughout the whole process. Here, we describe large-scale elemental profiling in Arabidopsis thaliana and other genetic model organisms using high-throughput analytical methodologies. We also include a description of workflow management and data storage systems. |
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 % |
|---|---|---|
| United Kingdom | 2 | 100% |
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 96 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Algeria | 1 | 1% |
| United States | 1 | 1% |
| Germany | 1 | 1% |
| Unknown | 93 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 21 | 22% |
| Student > Master | 14 | 15% |
| Student > Bachelor | 11 | 11% |
| Student > Ph. D. Student | 11 | 11% |
| Student > Doctoral Student | 7 | 7% |
| Other | 10 | 10% |
| Unknown | 22 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 50 | 52% |
| Biochemistry, Genetics and Molecular Biology | 5 | 5% |
| Engineering | 3 | 3% |
| Chemistry | 3 | 3% |
| Environmental Science | 2 | 2% |
| Other | 5 | 5% |
| Unknown | 28 | 29% |
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 13 March 2013.
All research outputs
#15,266,089
of 22,701,287 outputs
Outputs from Methods in molecular biology
#5,298
of 13,076 outputs
Outputs of similar age
#108,019
of 172,118 outputs
Outputs of similar age from Methods in molecular biology
#30
of 73 outputs
Altmetric has tracked 22,701,287 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,076 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 45th percentile – i.e., 45% 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 172,118 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 73 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 50% of its contemporaries.