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Mendeley readers
Attention Score in Context
| Title |
Genomic prediction of genetic merit using LD-based haplotypes in the Nordic Holstein population
|
|---|---|
| Published in |
BMC Genomics, December 2014
|
| DOI | 10.1186/1471-2164-15-1171 |
| Pubmed ID | |
| Authors |
Beatriz CD Cuyabano, Guosheng Su, Mogens S Lund |
| Abstract |
A haplotype approach to genomic prediction using high density data in dairy cattle as an alternative to single-marker methods is presented. With the assumption that haplotypes are in stronger linkage disequilibrium (LD) with quantitative trait loci (QTL) than single markers, this study focuses on the use of haplotype blocks (haploblocks) as explanatory variables for genomic prediction. Haploblocks were built based on the LD between markers, which allowed variable reduction. The haploblocks were then used to predict three economically important traits (milk protein, fertility and mastitis) in the Nordic Holstein population. |
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 % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 1% |
| France | 1 | 1% |
| Brazil | 1 | 1% |
| Unknown | 79 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 26 | 32% |
| Researcher | 13 | 16% |
| Student > Master | 11 | 13% |
| Student > Doctoral Student | 5 | 6% |
| Other | 5 | 6% |
| Other | 6 | 7% |
| Unknown | 16 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 44 | 54% |
| Biochemistry, Genetics and Molecular Biology | 7 | 9% |
| Veterinary Science and Veterinary Medicine | 2 | 2% |
| Computer Science | 2 | 2% |
| Mathematics | 2 | 2% |
| Other | 4 | 5% |
| Unknown | 21 | 26% |
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 23 December 2014.
All research outputs
#18,387,239
of 22,775,504 outputs
Outputs from BMC Genomics
#8,171
of 10,642 outputs
Outputs of similar age
#255,548
of 352,836 outputs
Outputs of similar age from BMC Genomics
#197
of 253 outputs
Altmetric has tracked 22,775,504 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,642 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 12th percentile – i.e., 12% 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 352,836 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 253 others from the same source and published within six weeks on either side of this one. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.