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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A whole genome long-range haplotype (WGLRH) test for detecting imprints of positive selection in human populations.
|
|---|---|
| Published in |
Bioinformatics, July 2006
|
| DOI | 10.1093/bioinformatics/btl365 |
| Pubmed ID | |
| Authors |
Chun Zhang, Dione K. Bailey, Tarif Awad, Guoying Liu, Guoliang Xing, Manqiu Cao, Venu Valmeekam, Jacques Retief, Hajime Matsuzaki, Margaret Taub, Mark Seielstad, Giulia C. Kennedy |
| Abstract |
The identification of signatures of positive selection can provide important insights into recent evolutionary history in human populations. Current methods mostly rely on allele frequency determination or focus on one or a small number of candidate chromosomal regions per study. With the availability of large-scale genotype data, efficient approaches for an unbiased whole genome scan are becoming necessary. |
X Demographics
The data shown below were collected from the profiles of 3 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 States | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 123 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 4 | 3% |
| United States | 2 | 2% |
| United Kingdom | 2 | 2% |
| Italy | 1 | <1% |
| Colombia | 1 | <1% |
| Germany | 1 | <1% |
| France | 1 | <1% |
| Unknown | 111 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 29 | 24% |
| Student > Ph. D. Student | 28 | 23% |
| Student > Master | 14 | 11% |
| Student > Bachelor | 7 | 6% |
| Professor > Associate Professor | 7 | 6% |
| Other | 17 | 14% |
| Unknown | 21 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 69 | 56% |
| Biochemistry, Genetics and Molecular Biology | 14 | 11% |
| Mathematics | 5 | 4% |
| Medicine and Dentistry | 4 | 3% |
| Computer Science | 3 | 2% |
| Other | 8 | 7% |
| Unknown | 20 | 16% |
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 24 January 2020.
All research outputs
#15,168,964
of 25,373,627 outputs
Outputs from Bioinformatics
#9,153
of 12,808 outputs
Outputs of similar age
#79,630
of 91,388 outputs
Outputs of similar age from Bioinformatics
#71
of 84 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 12,808 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. 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 91,388 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 84 others from the same source and published within six weeks on either side of this one. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.