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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Differential Evolution approach to detect recent admixture
|
|---|---|
| Published in |
BMC Genomics, June 2015
|
| DOI | 10.1186/1471-2164-16-s8-s9 |
| Pubmed ID | |
| Authors |
Konstantin Kozlov, Dmitri Chebotarev, Mehedi Hassan, Martin Triska, Petr Triska, Pavel Flegontov, Tatiana V Tatarinova |
| Abstract |
The genetic structure of human populations is extraordinarily complex and of fundamental importance to studies of anthropology, evolution, and medicine. As increasingly many individuals are of mixed origin, there is an unmet need for tools that can infer multiple origins. Misclassification of such individuals can lead to incorrect and costly misinterpretations of genomic data, primarily in disease studies and drug trials. We present an advanced tool to infer ancestry that can identify the biogeographic origins of highly mixed individuals. reAdmix can incorporate individual's knowledge of ancestors (e.g. having some ancestors from Turkey or a Scottish grandmother). reAdmix is an online tool available at http://chcb.saban-chla.usc.edu/reAdmix/. |
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 % |
|---|---|---|
| United States | 1 | 25% |
| Unknown | 3 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 50% |
| Members of the public | 2 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Philippines | 1 | 3% |
| United States | 1 | 3% |
| Unknown | 29 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 23% |
| Student > Ph. D. Student | 6 | 19% |
| Student > Bachelor | 3 | 10% |
| Professor > Associate Professor | 3 | 10% |
| Student > Master | 2 | 6% |
| Other | 1 | 3% |
| Unknown | 9 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 7 | 23% |
| Agricultural and Biological Sciences | 6 | 19% |
| Social Sciences | 3 | 10% |
| Computer Science | 2 | 6% |
| Immunology and Microbiology | 1 | 3% |
| Other | 3 | 10% |
| Unknown | 9 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 28 February 2022.
All research outputs
#7,616,848
of 23,221,875 outputs
Outputs from BMC Genomics
#3,646
of 10,726 outputs
Outputs of similar age
#89,974
of 265,219 outputs
Outputs of similar age from BMC Genomics
#91
of 250 outputs
Altmetric has tracked 23,221,875 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,726 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 59% of its peers.
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 265,219 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 57% of its contemporaries.
We're also able to compare this research output to 250 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 60% of its contemporaries.