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Mendeley readers
Attention Score in Context
| Title |
Dating the age of admixture via wavelet transform analysis of genome-wide data
|
|---|---|
| Published in |
Genome Biology, February 2011
|
| DOI | 10.1186/gb-2011-12-2-r19 |
| Pubmed ID | |
| Authors |
Irina Pugach, Rostislav Matveyev, Andreas Wollstein, Manfred Kayser, Mark Stoneking |
| Abstract |
We describe a PCA-based genome scan approach to analyze genome-wide admixture structure, and introduce wavelet transform analysis as a method for estimating the time of admixture. We test the wavelet transform method with simulations and apply it to genome-wide SNP data from eight admixed human populations. The wavelet transform method offers better resolution than existing methods for dating admixture, and can be applied to either SNP or sequence data from humans or other species. |
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 % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 141 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 7 | 5% |
| France | 1 | <1% |
| Brazil | 1 | <1% |
| Uruguay | 1 | <1% |
| United Kingdom | 1 | <1% |
| Finland | 1 | <1% |
| Unknown | 129 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 41 | 29% |
| Student > Ph. D. Student | 39 | 28% |
| Student > Master | 13 | 9% |
| Professor > Associate Professor | 8 | 6% |
| Professor | 7 | 5% |
| Other | 21 | 15% |
| Unknown | 12 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 82 | 58% |
| Biochemistry, Genetics and Molecular Biology | 23 | 16% |
| Computer Science | 6 | 4% |
| Engineering | 5 | 4% |
| Medicine and Dentistry | 3 | 2% |
| Other | 6 | 4% |
| Unknown | 16 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. 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 14 September 2017.
All research outputs
#4,587,886
of 25,373,627 outputs
Outputs from Genome Biology
#2,724
of 4,467 outputs
Outputs of similar age
#21,756
of 117,745 outputs
Outputs of similar age from Genome Biology
#15
of 32 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one is in the 39th percentile – i.e., 39% 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 117,745 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 81% of its contemporaries.
We're also able to compare this research output to 32 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 53% of its contemporaries.