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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A simple method for estimating genetic diversity in large populations from finite sample sizes
|
|---|---|
| Published in |
BMC Genomic Data, December 2009
|
| DOI | 10.1186/1471-2156-10-84 |
| Pubmed ID | |
| Authors |
Stanislav Bashalkhanov, Madhav Pandey, Om P Rajora |
| Abstract |
Sample size is one of the critical factors affecting the accuracy of the estimation of population genetic diversity parameters. Small sample sizes often lead to significant errors in determining the allelic richness, which is one of the most important and commonly used estimators of genetic diversity in populations. Correct estimation of allelic richness in natural populations is challenging since they often do not conform to model assumptions. Here, we introduce a simple and robust approach to estimate the genetic diversity in large natural populations based on the empirical data for finite sample sizes. |
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 % |
|---|---|---|
| Unknown | 2 | 100% |
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 251 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Italy | 3 | 1% |
| Brazil | 3 | 1% |
| Netherlands | 2 | <1% |
| Chile | 1 | <1% |
| France | 1 | <1% |
| Switzerland | 1 | <1% |
| Germany | 1 | <1% |
| Australia | 1 | <1% |
| Sweden | 1 | <1% |
| Other | 5 | 2% |
| Unknown | 232 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 64 | 25% |
| Researcher | 51 | 20% |
| Student > Master | 29 | 12% |
| Student > Doctoral Student | 16 | 6% |
| Student > Bachelor | 16 | 6% |
| Other | 43 | 17% |
| Unknown | 32 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 140 | 56% |
| Biochemistry, Genetics and Molecular Biology | 31 | 12% |
| Environmental Science | 19 | 8% |
| Computer Science | 3 | 1% |
| Arts and Humanities | 3 | 1% |
| Other | 12 | 5% |
| Unknown | 43 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 August 2016.
All research outputs
#4,158,218
of 25,373,627 outputs
Outputs from BMC Genomic Data
#129
of 1,204 outputs
Outputs of similar age
#22,308
of 172,797 outputs
Outputs of similar age from BMC Genomic Data
#3
of 6 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 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,204 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done well, scoring higher than 89% 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 172,797 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 87% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.