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Mendeley readers
Attention Score in Context
| Title |
Coupled mutation finder: A new entropy-based method quantifying phylogenetic noise for the detection of compensatory mutations
|
|---|---|
| Published in |
BMC Bioinformatics, September 2012
|
| DOI | 10.1186/1471-2105-13-225 |
| Pubmed ID | |
| Authors |
Mehmet Gültas, Martin Haubrock, Nesrin Tüysüz, Stephan Waack |
| Abstract |
The detection of significant compensatory mutation signals in multiple sequence alignments (MSAs) is often complicated by noise. A challenging problem in bioinformatics is remains the separation of significant signals between two or more non-conserved residue sites from the phylogenetic noise and unrelated pair signals. Determination of these non-conserved residue sites is as important as the recognition of strictly conserved positions for understanding of the structural basis of protein functions and identification of functionally important residue regions. In this study, we developed a new method, the Coupled Mutation Finder (CMF) quantifying the phylogenetic noise for the detection of compensatory mutations. |
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 % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 2% |
| United States | 1 | 2% |
| Saudi Arabia | 1 | 2% |
| Unknown | 38 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 14 | 34% |
| Researcher | 13 | 32% |
| Student > Master | 3 | 7% |
| Student > Doctoral Student | 2 | 5% |
| Student > Bachelor | 2 | 5% |
| Other | 6 | 15% |
| Unknown | 1 | 2% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 24 | 59% |
| Biochemistry, Genetics and Molecular Biology | 4 | 10% |
| Computer Science | 4 | 10% |
| Physics and Astronomy | 3 | 7% |
| Chemical Engineering | 1 | 2% |
| Other | 3 | 7% |
| Unknown | 2 | 5% |
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 September 2012.
All research outputs
#18,314,922
of 22,678,224 outputs
Outputs from BMC Bioinformatics
#6,285
of 7,249 outputs
Outputs of similar age
#128,375
of 168,561 outputs
Outputs of similar age from BMC Bioinformatics
#75
of 93 outputs
Altmetric has tracked 22,678,224 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,249 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 5th percentile – i.e., 5% of its peers scored the same or lower than it.
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 168,561 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 93 others from the same source and published within six weeks on either side of this one. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.