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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A unifying model of genome evolution under parsimony
|
|---|---|
| Published in |
BMC Bioinformatics, June 2014
|
| DOI | 10.1186/1471-2105-15-206 |
| Pubmed ID | |
| Authors |
Benedict Paten, Daniel R Zerbino, Glenn Hickey, David Haussler |
| Abstract |
Parsimony and maximum likelihood methods of phylogenetic tree estimation and parsimony methods for genome rearrangements are central to the study of genome evolution yet to date they have largely been pursued in isolation. |
X Demographics
The data shown below were collected from the profiles of 11 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 4 | 36% |
| United States | 2 | 18% |
| Norway | 1 | 9% |
| Canada | 1 | 9% |
| Unknown | 3 | 27% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 55% |
| Scientists | 4 | 36% |
| Science communicators (journalists, bloggers, editors) | 1 | 9% |
Mendeley readers
The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 2 | 4% |
| Netherlands | 1 | 2% |
| Norway | 1 | 2% |
| Brazil | 1 | 2% |
| United Kingdom | 1 | 2% |
| Spain | 1 | 2% |
| United States | 1 | 2% |
| Unknown | 40 | 83% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 13 | 27% |
| Student > Ph. D. Student | 11 | 23% |
| Student > Postgraduate | 5 | 10% |
| Professor | 4 | 8% |
| Student > Bachelor | 3 | 6% |
| Other | 9 | 19% |
| Unknown | 3 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 25 | 52% |
| Computer Science | 12 | 25% |
| Biochemistry, Genetics and Molecular Biology | 4 | 8% |
| Mathematics | 1 | 2% |
| Chemical Engineering | 1 | 2% |
| Other | 1 | 2% |
| Unknown | 4 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 12. 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 16 November 2023.
All research outputs
#2,941,502
of 25,090,809 outputs
Outputs from BMC Bioinformatics
#867
of 7,646 outputs
Outputs of similar age
#28,098
of 234,179 outputs
Outputs of similar age from BMC Bioinformatics
#19
of 156 outputs
Altmetric has tracked 25,090,809 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,646 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 88% 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 234,179 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 87% of its contemporaries.
We're also able to compare this research output to 156 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.