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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Multiple consensus trees: a method to separate divergent genes
|
|---|---|
| Published in |
BMC Bioinformatics, February 2013
|
| DOI | 10.1186/1471-2105-14-46 |
| Pubmed ID | |
| Authors |
Alain Guénoche |
| Abstract |
It is generally admitted that the species tree cannot be inferred from the genetic sequences of a single gene because the evolution of different genes, and thus the gene tree topologies, may vary substantially. Gene trees can differ, for example, because of horizontal transfer events or because some of them correspond to paralogous instead of orthologous sequences. A variety of methods has been proposed to tackle the problem of the reconciliation of gene trees in order to reconstruct a species tree. When the taxa in all the trees are identical, the problem can be stated as a consensus tree problem. |
X Demographics
The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 14% |
| Norway | 1 | 14% |
| United Kingdom | 1 | 14% |
| Unknown | 4 | 57% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 57% |
| Scientists | 2 | 29% |
| Practitioners (doctors, other healthcare professionals) | 1 | 14% |
Mendeley readers
The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 7% |
| Sweden | 1 | 2% |
| Germany | 1 | 2% |
| Russia | 1 | 2% |
| United Kingdom | 1 | 2% |
| Unknown | 38 | 84% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 13 | 29% |
| Student > Ph. D. Student | 11 | 24% |
| Student > Doctoral Student | 4 | 9% |
| Student > Bachelor | 4 | 9% |
| Lecturer | 4 | 9% |
| Other | 9 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 32 | 71% |
| Computer Science | 5 | 11% |
| Biochemistry, Genetics and Molecular Biology | 4 | 9% |
| Linguistics | 2 | 4% |
| Engineering | 1 | 2% |
| Other | 0 | 0% |
| Unknown | 1 | 2% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 04 March 2017.
All research outputs
#7,622,789
of 23,881,329 outputs
Outputs from BMC Bioinformatics
#2,932
of 7,454 outputs
Outputs of similar age
#84,645
of 291,046 outputs
Outputs of similar age from BMC Bioinformatics
#59
of 135 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 7,454 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. 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 291,046 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 69% of its contemporaries.
We're also able to compare this research output to 135 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 54% of its contemporaries.