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X Demographics
Mendeley readers
Attention Score in Context
| Title |
QTL fine mapping with Bayes C(π): a simulation study
|
|---|---|
| Published in |
Genetics Selection Evolution, June 2013
|
| DOI | 10.1186/1297-9686-45-19 |
| Pubmed ID | |
| Authors |
Irene van den Berg, Sébastien Fritz, Didier Boichard |
| Abstract |
Accurate QTL mapping is a prerequisite in the search for causative mutations. Bayesian genomic selection models that analyse many markers simultaneously should provide more accurate QTL detection results than single-marker models. Our objectives were to (a) evaluate by simulation the influence of heritability, number of QTL and number of records on the accuracy of QTL mapping with Bayes Cπ and Bayes C; (b) estimate the QTL status (homozygous vs. heterozygous) of the individuals analysed. This study focussed on the ten largest detected QTL, assuming they are candidates for further characterization. |
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 | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Science communicators (journalists, bloggers, editors) | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Colombia | 1 | 1% |
| Germany | 1 | 1% |
| Brazil | 1 | 1% |
| India | 1 | 1% |
| United States | 1 | 1% |
| Poland | 1 | 1% |
| Unknown | 66 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 22 | 31% |
| Student > Ph. D. Student | 16 | 22% |
| Student > Master | 13 | 18% |
| Student > Doctoral Student | 7 | 10% |
| Professor > Associate Professor | 2 | 3% |
| Other | 5 | 7% |
| Unknown | 7 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 48 | 67% |
| Biochemistry, Genetics and Molecular Biology | 6 | 8% |
| Mathematics | 2 | 3% |
| Unspecified | 1 | 1% |
| Veterinary Science and Veterinary Medicine | 1 | 1% |
| Other | 3 | 4% |
| Unknown | 11 | 15% |
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 10 July 2013.
All research outputs
#17,283,763
of 25,371,288 outputs
Outputs from Genetics Selection Evolution
#550
of 822 outputs
Outputs of similar age
#132,817
of 209,373 outputs
Outputs of similar age from Genetics Selection Evolution
#4
of 12 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% 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 is in the 22nd percentile – i.e., 22% 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 209,373 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 12 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.