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Attention Score in Context
| Title |
Predicting complex traits using a diffusion kernel on genetic markers with an application to dairy cattle and wheat data
|
|---|---|
| Published in |
Genetics Selection Evolution, June 2013
|
| DOI | 10.1186/1297-9686-45-17 |
| Pubmed ID | |
| Authors |
Gota Morota, Masanori Koyama, Guilherme J M Rosa, Kent A Weigel, Daniel Gianola |
| Abstract |
Arguably, genotypes and phenotypes may be linked in functional forms that are not well addressed by the linear additive models that are standard in quantitative genetics. Therefore, developing statistical learning models for predicting phenotypic values from all available molecular information that are capable of capturing complex genetic network architectures is of great importance. Bayesian kernel ridge regression is a non-parametric prediction model proposed for this purpose. Its essence is to create a spatial distance-based relationship matrix called a kernel. Although the set of all single nucleotide polymorphism genotype configurations on which a model is built is finite, past research has mainly used a Gaussian kernel. |
X Demographics
The data shown below were collected from the profiles of 4 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 | 50% |
| France | 1 | 25% |
| United States | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 50% |
| Practitioners (doctors, other healthcare professionals) | 1 | 25% |
| Science communicators (journalists, bloggers, editors) | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 1 | 2% |
| Unknown | 47 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 17 | 35% |
| Researcher | 7 | 15% |
| Student > Doctoral Student | 4 | 8% |
| Student > Master | 4 | 8% |
| Student > Bachelor | 2 | 4% |
| Other | 7 | 15% |
| Unknown | 7 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 26 | 54% |
| Biochemistry, Genetics and Molecular Biology | 5 | 10% |
| Computer Science | 5 | 10% |
| Mathematics | 2 | 4% |
| Veterinary Science and Veterinary Medicine | 1 | 2% |
| Other | 2 | 4% |
| Unknown | 7 | 15% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 19 July 2013.
All research outputs
#8,534,976
of 25,374,647 outputs
Outputs from Genetics Selection Evolution
#303
of 822 outputs
Outputs of similar age
#71,664
of 209,499 outputs
Outputs of similar age from Genetics Selection Evolution
#3
of 11 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 822 research outputs from this source. They receive a mean Attention Score of 4.1. This one has gotten more attention than average, scoring higher than 53% 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 209,499 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 11 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 72% of its contemporaries.