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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Genome-enabled predictions for binomial traits in sugar beet populations
|
|---|---|
| Published in |
BMC Genomic Data, July 2014
|
| DOI | 10.1186/1471-2156-15-87 |
| Pubmed ID | |
| Authors |
Filippo Biscarini, Piergiorgio Stevanato, Chiara Broccanello, Alessandra Stella, Massimo Saccomani |
| Abstract |
Genomic information can be used to predict not only continuous but also categorical (e.g. binomial) traits. Several traits of interest in human medicine and agriculture present a discrete distribution of phenotypes (e.g. disease status). Root vigor in sugar beet (B. vulgaris) is an example of binomial trait of agronomic importance. In this paper, a panel of 192 SNPs (single nucleotide polymorphisms) was used to genotype 124 sugar beet individual plants from 18 lines, and to classify them as showing "high" or "low" root vigor. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Denmark | 1 | 3% |
| Germany | 1 | 3% |
| Belgium | 1 | 3% |
| Unknown | 27 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 27% |
| Student > Ph. D. Student | 7 | 23% |
| Student > Master | 4 | 13% |
| Student > Doctoral Student | 3 | 10% |
| Professor > Associate Professor | 2 | 7% |
| Other | 3 | 10% |
| Unknown | 3 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 19 | 63% |
| Biochemistry, Genetics and Molecular Biology | 3 | 10% |
| Computer Science | 1 | 3% |
| Mathematics | 1 | 3% |
| Unknown | 6 | 20% |
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 05 November 2014.
All research outputs
#22,759,452
of 25,374,647 outputs
Outputs from BMC Genomic Data
#1,008
of 1,204 outputs
Outputs of similar age
#205,528
of 239,414 outputs
Outputs of similar age from BMC Genomic Data
#19
of 25 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,204 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 1st percentile – i.e., 1% 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 239,414 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.