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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Identification of polymorphic inversions from genotypes
|
|---|---|
| Published in |
BMC Bioinformatics, February 2012
|
| DOI | 10.1186/1471-2105-13-28 |
| Pubmed ID | |
| Authors |
Alejandro Cáceres, Suzanne S Sindi, Benjamin J Raphael, Mario Cáceres, Juan R González |
| Abstract |
Polymorphic inversions are a source of genetic variability with a direct impact on recombination frequencies. Given the difficulty of their experimental study, computational methods have been developed to infer their existence in a large number of individuals using genome-wide data of nucleotide variation. Methods based on haplotype tagging of known inversions attempt to classify individuals as having a normal or inverted allele. Other methods that measure differences between linkage disequilibrium attempt to identify regions with inversions but unable to classify subjects accurately, an essential requirement for association studies. |
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% |
| Germany | 1 | 33% |
| Australia | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 103 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 4 | 4% |
| Germany | 1 | <1% |
| Sweden | 1 | <1% |
| Netherlands | 1 | <1% |
| Canada | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 94 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 31 | 30% |
| Researcher | 29 | 28% |
| Student > Master | 13 | 13% |
| Student > Bachelor | 7 | 7% |
| Student > Doctoral Student | 2 | 2% |
| Other | 9 | 9% |
| Unknown | 12 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 51 | 50% |
| Biochemistry, Genetics and Molecular Biology | 25 | 24% |
| Veterinary Science and Veterinary Medicine | 2 | 2% |
| Computer Science | 2 | 2% |
| Mathematics | 2 | 2% |
| Other | 8 | 8% |
| Unknown | 13 | 13% |
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 08 March 2022.
All research outputs
#14,547,784
of 23,298,349 outputs
Outputs from BMC Bioinformatics
#4,818
of 7,379 outputs
Outputs of similar age
#156,138
of 250,228 outputs
Outputs of similar age from BMC Bioinformatics
#41
of 58 outputs
Altmetric has tracked 23,298,349 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,379 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 30th percentile – i.e., 30% 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 250,228 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 58 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.