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Attention Score in Context
| Title |
EUCALYPT: efficient tree reconciliation enumerator
|
|---|---|
| Published in |
Algorithms for Molecular Biology, January 2015
|
| DOI | 10.1186/s13015-014-0031-3 |
| Pubmed ID | |
| Authors |
Beatrice Donati, Christian Baudet, Blerina Sinaimeri, Pierluigi Crescenzi, Marie-France Sagot |
| Abstract |
Phylogenetic tree reconciliation is the approach of choice for investigating the coevolution of sets of organisms such as hosts and parasites. It consists in a mapping between the parasite tree and the host tree using event-based maximum parsimony. Given a cost model for the events, many optimal reconciliations are however possible. Any further biological interpretation of them must therefore take this into account, making the capacity to enumerate all optimal solutions a crucial point. Only two algorithms currently exist that attempt such enumeration; in one case not all possible solutions are produced while in the other not all cost vectors are currently handled. The objective of this paper is two-fold. The first is to fill this gap, and the second is to test whether the number of solutions generally observed can be an issue in terms of interpretation. |
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 % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 22 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 27% |
| Professor | 5 | 23% |
| Student > Ph. D. Student | 4 | 18% |
| Student > Master | 2 | 9% |
| Student > Doctoral Student | 2 | 9% |
| Other | 0 | 0% |
| Unknown | 3 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 8 | 36% |
| Computer Science | 5 | 23% |
| Linguistics | 2 | 9% |
| Biochemistry, Genetics and Molecular Biology | 2 | 9% |
| Environmental Science | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 3 | 14% |
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 05 February 2015.
All research outputs
#17,743,721
of 22,786,087 outputs
Outputs from Algorithms for Molecular Biology
#173
of 264 outputs
Outputs of similar age
#241,423
of 351,563 outputs
Outputs of similar age from Algorithms for Molecular Biology
#6
of 13 outputs
Altmetric has tracked 22,786,087 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 264 research outputs from this source. They receive a mean Attention Score of 3.2. This one is in the 25th percentile – i.e., 25% 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 351,563 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.