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X Demographics
Mendeley readers
Attention Score in Context
| Title |
GVCBLUP: a computer package for genomic prediction and variance component estimation of additive and dominance effects
|
|---|---|
| Published in |
BMC Bioinformatics, August 2014
|
| DOI | 10.1186/1471-2105-15-270 |
| Pubmed ID | |
| Authors |
Chunkao Wang, Dzianis Prakapenka, Shengwen Wang, Sujata Pulugurta, Hakizumwami Birali Runesha, Yang Da |
| Abstract |
Dominance effect may play an important role in genetic variation of complex traits. Full featured and easy-to-use computing tools for genomic prediction and variance component estimation of additive and dominance effects using genome-wide single nucleotide polymorphism (SNP) markers are necessary to understand dominance contribution to a complex trait and to utilize dominance for selecting individuals with favorable genetic potential. |
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 % |
|---|---|---|
| Unknown | 4 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 75% |
| Members of the public | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 1% |
| United States | 1 | 1% |
| Sweden | 1 | 1% |
| Unknown | 67 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 19 | 27% |
| Researcher | 9 | 13% |
| Student > Master | 8 | 11% |
| Student > Doctoral Student | 7 | 10% |
| Other | 4 | 6% |
| Other | 8 | 11% |
| Unknown | 15 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 34 | 49% |
| Computer Science | 8 | 11% |
| Biochemistry, Genetics and Molecular Biology | 4 | 6% |
| Veterinary Science and Veterinary Medicine | 1 | 1% |
| Psychology | 1 | 1% |
| Other | 4 | 6% |
| Unknown | 18 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 October 2014.
All research outputs
#14,783,222
of 22,759,618 outputs
Outputs from BMC Bioinformatics
#5,040
of 7,273 outputs
Outputs of similar age
#126,716
of 230,536 outputs
Outputs of similar age from BMC Bioinformatics
#85
of 120 outputs
Altmetric has tracked 22,759,618 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,273 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 26th percentile – i.e., 26% 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 230,536 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 120 others from the same source and published within six weeks on either side of this one. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.