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X Demographics
Mendeley readers
Attention Score in Context
| Title |
MergeAlign: improving multiple sequence alignment performance by dynamic reconstruction of consensus multiple sequence alignments
|
|---|---|
| Published in |
BMC Bioinformatics, May 2012
|
| DOI | 10.1186/1471-2105-13-117 |
| Pubmed ID | |
| Authors |
Peter W Collingridge, Steven Kelly |
| Abstract |
The generation of multiple sequence alignments (MSAs) is a crucial step for many bioinformatic analyses. Thus improving MSA accuracy and identifying potential errors in MSAs is important for a wide range of post-genomic research. We present a novel method called MergeAlign which constructs consensus MSAs from multiple independent MSAs and assigns an alignment precision score to each column. |
X Demographics
The data shown below were collected from the profiles of 4 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 | 3 | 75% |
| United States | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 75% |
| Members of the public | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 107 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 2% |
| United Kingdom | 2 | 2% |
| Hungary | 1 | <1% |
| Germany | 1 | <1% |
| Brazil | 1 | <1% |
| Spain | 1 | <1% |
| Ukraine | 1 | <1% |
| Unknown | 98 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 33 | 31% |
| Student > Ph. D. Student | 27 | 25% |
| Student > Master | 9 | 8% |
| Student > Doctoral Student | 7 | 7% |
| Student > Bachelor | 7 | 7% |
| Other | 20 | 19% |
| Unknown | 4 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 58 | 54% |
| Biochemistry, Genetics and Molecular Biology | 20 | 19% |
| Computer Science | 12 | 11% |
| Mathematics | 3 | 3% |
| Medicine and Dentistry | 2 | 2% |
| Other | 4 | 4% |
| Unknown | 8 | 7% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 04 February 2021.
All research outputs
#3,098,136
of 22,668,244 outputs
Outputs from BMC Bioinformatics
#1,136
of 7,247 outputs
Outputs of similar age
#21,797
of 165,091 outputs
Outputs of similar age from BMC Bioinformatics
#23
of 107 outputs
Altmetric has tracked 22,668,244 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 7,247 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 84% 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 165,091 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 86% of its contemporaries.
We're also able to compare this research output to 107 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.