| Title |
Linear time minimum segmentation enables scalable founder reconstruction
|
|---|---|
| Published in |
Algorithms for Molecular Biology, May 2019
|
| DOI | 10.1186/s13015-019-0147-6 |
| Pubmed ID | |
| Authors |
Tuukka Norri, Bastien Cazaux, Dmitry Kosolobov, Veli Mäkinen |
X Demographics
The data shown below were collected from the profiles of 12 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 | 33% |
| United States | 1 | 8% |
| Unknown | 7 | 58% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 58% |
| Scientists | 4 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 10 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 3 | 30% |
| Professor | 2 | 20% |
| Student > Bachelor | 1 | 10% |
| Student > Doctoral Student | 1 | 10% |
| Unknown | 3 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 5 | 50% |
| Chemical Engineering | 1 | 10% |
| Biochemistry, Genetics and Molecular Biology | 1 | 10% |
| Engineering | 1 | 10% |
| Unknown | 2 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. 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 06 June 2019.
All research outputs
#2,830,546
of 26,017,215 outputs
Outputs from Algorithms for Molecular Biology
#14
of 269 outputs
Outputs of similar age
#58,476
of 369,202 outputs
Outputs of similar age from Algorithms for Molecular Biology
#1
of 3 outputs
Altmetric has tracked 26,017,215 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 269 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done particularly well, scoring higher than 94% 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 369,202 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 83% of its contemporaries.
We're also able to compare this research output to 3 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