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Mendeley readers
Attention Score in Context
| Title |
A hybrid next generation transcript sequencing-based approach to identify allelic and homeolog-specific single nucleotide polymorphisms in allotetraploid white clover
|
|---|---|
| Published in |
BMC Genomics, February 2013
|
| DOI | 10.1186/1471-2164-14-100 |
| Pubmed ID | |
| Authors |
Istvan Nagy, Susanne Barth, Jeanne Mehenni-Ciz, Michael T Abberton, Dan Milbourne |
| Abstract |
White clover (Trifolium repens L.) is an allotetraploid species possessing two highly collinear ancestral sub-genomes. The apparent existence of highly similar homeolog copies for the majority of genes in white clover is problematic for the development of genome-based resources in the species. This is especially true for the development of genetic markers based on single nucleotide polymorphisms (SNPs), since it is difficult to distinguish between homeolog-specific and allelic variants. Robust methods for categorising single nucleotide variants as allelic or homeolog-specific in large transcript datasets are required. We illustrate one potential approach in this study. |
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 % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 8% |
| United Kingdom | 1 | 3% |
| Netherlands | 1 | 3% |
| Sweden | 1 | 3% |
| Unknown | 32 | 84% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 13 | 34% |
| Student > Ph. D. Student | 10 | 26% |
| Student > Master | 3 | 8% |
| Student > Doctoral Student | 2 | 5% |
| Professor | 2 | 5% |
| Other | 4 | 11% |
| Unknown | 4 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 26 | 68% |
| Biochemistry, Genetics and Molecular Biology | 3 | 8% |
| Mathematics | 1 | 3% |
| Economics, Econometrics and Finance | 1 | 3% |
| Physics and Astronomy | 1 | 3% |
| Other | 0 | 0% |
| Unknown | 6 | 16% |
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 13 February 2013.
All research outputs
#18,329,207
of 22,696,971 outputs
Outputs from BMC Genomics
#8,146
of 10,616 outputs
Outputs of similar age
#222,707
of 287,582 outputs
Outputs of similar age from BMC Genomics
#272
of 358 outputs
Altmetric has tracked 22,696,971 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,616 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 12th percentile – i.e., 12% 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 287,582 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 358 others from the same source and published within six weeks on either side of this one. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.