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Attention Score in Context
| Title |
Inferring duplication episodes from unrooted gene trees
|
|---|---|
| Published in |
BMC Genomics, May 2018
|
| DOI | 10.1186/s12864-018-4623-z |
| Pubmed ID | |
| Authors |
Jarosław Paszek, Paweł Górecki |
| Abstract |
One of evolutionary molecular biology fundamental issues is to discover genomic duplication events and their correspondence to the species tree. Such events can be reconstructed by clustering single gene duplications inferred by reconciling a set of gene trees with a species tree. Here we propose the first solutions to the genomic duplication problem in which every reconciliation with the minimal number of single gene duplications is allowed and the method of clustering called minimum episodes under the assumption that input gene trees are unrooted. We showed new theoretical properties of unrooted reconciliation for the duplication cost and apply them to design several exact and heuristic algorithms for solving the problem. Our evaluation study on empirical dataset confirmed several genomic duplication events from the literature and demonstrate that algorithms can be successfully applied. |
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 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 7 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 3 | 43% |
| Student > Bachelor | 1 | 14% |
| Student > Doctoral Student | 1 | 14% |
| Researcher | 1 | 14% |
| Professor > Associate Professor | 1 | 14% |
| Other | 0 | 0% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 3 | 43% |
| Agricultural and Biological Sciences | 2 | 29% |
| Biochemistry, Genetics and Molecular Biology | 1 | 14% |
| Unknown | 1 | 14% |
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 13 May 2018.
All research outputs
#20,488,697
of 23,051,185 outputs
Outputs from BMC Genomics
#9,326
of 10,699 outputs
Outputs of similar age
#288,388
of 327,709 outputs
Outputs of similar age from BMC Genomics
#211
of 250 outputs
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So far Altmetric has tracked 10,699 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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