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X Demographics
Mendeley readers
Attention Score in Context
| Title |
phylotree.js - a JavaScript library for application development and interactive data visualization in phylogenetics
|
|---|---|
| Published in |
BMC Bioinformatics, July 2018
|
| DOI | 10.1186/s12859-018-2283-2 |
| Pubmed ID | |
| Authors |
Stephen D. Shank, Steven Weaver, Sergei L. Kosakovsky Pond |
| Abstract |
While several JavaScript packages for visualizing phylogenetic trees exist, most are best characterized as frameworks that are designed with a specific set of tasks in mind. Extending such packages to use cases that are not available as features often ends up being difficult. Moreover, existing packages tend to produce standalone widgets that are not designed to serve as middleware, as opposed to flexible tools that can integrate with other components of an application. phylotree.js is a library that extends the popular data visualization framework d3.js, and is suitable for building JavaScript applications where users can view and interact with phylogenetic trees. The effects of such interactions can be captured and communicated to other package components, making it possible to engineer complex and responsive applications that include phylogenetic trees. phylotree.js implements several abstractions in addition to features, and comes with a documented application programming interface, thus promoting interoperability and extensibility. Example applications include a tool to visualize and annotate phylogenetic trees, a web application for comparative sequence analysis, a structural viewer that interacts with a large phylogenetic tree, and an interactive tanglegram. phylotree.js is a useful tool and application module for a variety of computational biology software applications. The code is available on Github and is released under the MIT license. |
X Demographics
The data shown below were collected from the profiles of 14 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 2 | 14% |
| Switzerland | 1 | 7% |
| United Kingdom | 1 | 7% |
| Germany | 1 | 7% |
| Norway | 1 | 7% |
| United States | 1 | 7% |
| Unknown | 7 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 9 | 64% |
| Scientists | 5 | 36% |
Mendeley readers
The data shown below were compiled from readership statistics for 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 76 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 17 | 22% |
| Student > Ph. D. Student | 11 | 14% |
| Student > Master | 8 | 11% |
| Student > Bachelor | 6 | 8% |
| Student > Doctoral Student | 4 | 5% |
| Other | 9 | 12% |
| Unknown | 21 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 16 | 21% |
| Biochemistry, Genetics and Molecular Biology | 15 | 20% |
| Computer Science | 8 | 11% |
| Immunology and Microbiology | 2 | 3% |
| Arts and Humanities | 2 | 3% |
| Other | 10 | 13% |
| Unknown | 23 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 03 September 2021.
All research outputs
#3,145,494
of 24,272,486 outputs
Outputs from BMC Bioinformatics
#1,040
of 7,510 outputs
Outputs of similar age
#61,955
of 334,062 outputs
Outputs of similar age from BMC Bioinformatics
#18
of 98 outputs
Altmetric has tracked 24,272,486 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,510 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 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 334,062 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 81% of its contemporaries.
We're also able to compare this research output to 98 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.