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Mendeley readers
Attention Score in Context
| Title |
Computing the skewness of the phylogenetic mean pairwise distance in linear time
|
|---|---|
| Published in |
Algorithms for Molecular Biology, June 2014
|
| DOI | 10.1186/1748-7188-9-15 |
| Pubmed ID | |
| Authors |
Constantinos Tsirogiannis, Brody Sandel |
| Abstract |
The phylogenetic Mean Pairwise Distance (MPD) is one of the most popular measures for computing the phylogenetic distance between a given group of species. More specifically, for a phylogenetic tree [Formula: see text] and for a set of species R represented by a subset of the leaf nodes of [Formula: see text], the MPD of R is equal to the average cost of all possible simple paths in [Formula: see text] that connect pairs of nodes in R. Among other phylogenetic measures, the MPD is used as a tool for deciding if the species of a given group R are closely related. To do this, it is important to compute not only the value of the MPD for this group but also the expectation, the variance, and the skewness of this metric. Although efficient algorithms have been developed for computing the expectation and the variance the MPD, there has been no approach so far for computing the skewness of this measure. |
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 % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Russia | 1 | 7% |
| Unknown | 14 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 27% |
| Student > Ph. D. Student | 2 | 13% |
| Student > Doctoral Student | 1 | 7% |
| Student > Bachelor | 1 | 7% |
| Student > Master | 1 | 7% |
| Other | 1 | 7% |
| Unknown | 5 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 5 | 33% |
| Environmental Science | 2 | 13% |
| Biochemistry, Genetics and Molecular Biology | 1 | 7% |
| Computer Science | 1 | 7% |
| Earth and Planetary Sciences | 1 | 7% |
| Other | 0 | 0% |
| Unknown | 5 | 33% |
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 30 June 2014.
All research outputs
#18,373,874
of 22,757,541 outputs
Outputs from Algorithms for Molecular Biology
#197
of 264 outputs
Outputs of similar age
#163,760
of 228,190 outputs
Outputs of similar age from Algorithms for Molecular Biology
#5
of 5 outputs
Altmetric has tracked 22,757,541 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 264 research outputs from this source. They receive a mean Attention Score of 3.2. 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 228,190 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one.