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Mendeley readers
Attention Score in Context
| Title |
Jane: a new tool for the cophylogeny reconstruction problem
|
|---|---|
| Published in |
Algorithms for Molecular Biology, February 2010
|
| DOI | 10.1186/1748-7188-5-16 |
| Pubmed ID | |
| Authors |
Chris Conow, Daniel Fielder, Yaniv Ovadia, Ran Libeskind-Hadas |
| Abstract |
This paper describes the theory and implementation of a new software tool, called Jane, for the study of historical associations. This problem arises in parasitology (associations of hosts and parasites), molecular systematics (associations of orderings and genes), and biogeography (associations of regions and orderings). The underlying problem is that of reconciling pairs of trees subject to biologically plausible events and costs associated with these events. Existing software tools for this problem have strengths and limitations, and the new Jane tool described here provides functionality that complements existing tools. |
Mendeley readers
The data shown below were compiled from readership statistics for 260 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 2% |
| Spain | 3 | 1% |
| Germany | 2 | <1% |
| Australia | 2 | <1% |
| United Kingdom | 2 | <1% |
| France | 1 | <1% |
| Sweden | 1 | <1% |
| Colombia | 1 | <1% |
| Turkey | 1 | <1% |
| Other | 2 | <1% |
| Unknown | 239 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 60 | 23% |
| Researcher | 48 | 18% |
| Student > Master | 43 | 17% |
| Student > Bachelor | 21 | 8% |
| Professor > Associate Professor | 15 | 6% |
| Other | 50 | 19% |
| Unknown | 23 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 148 | 57% |
| Biochemistry, Genetics and Molecular Biology | 31 | 12% |
| Computer Science | 14 | 5% |
| Environmental Science | 12 | 5% |
| Immunology and Microbiology | 5 | 2% |
| Other | 18 | 7% |
| Unknown | 32 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 12 March 2014.
All research outputs
#4,406,443
of 22,747,498 outputs
Outputs from Algorithms for Molecular Biology
#36
of 264 outputs
Outputs of similar age
#26,296
of 165,219 outputs
Outputs of similar age from Algorithms for Molecular Biology
#1
of 5 outputs
Altmetric has tracked 22,747,498 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 264 research outputs from this source. They receive a mean Attention Score of 3.2. This one has done well, scoring higher than 86% 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 165,219 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 84% of its contemporaries.
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. This one has scored higher than all of them