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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Improvement of domain-level ortholog clustering by optimizing domain-specific sum-of-pairs score
|
|---|---|
| Published in |
BMC Bioinformatics, May 2014
|
| DOI | 10.1186/1471-2105-15-148 |
| Pubmed ID | |
| Authors |
Hirokazu Chiba, Ikuo Uchiyama |
| Abstract |
Identification of ortholog groups is a crucial step in comparative analysis of multiple genomes. Although several computational methods have been developed to create ortholog groups, most of those methods do not evaluate orthology at the sub-gene level. In our method for domain-level ortholog clustering, DomClust, proteins are split into domains on the basis of alignment boundaries identified by all-against-all pairwise comparison, but it often fails to determine appropriate boundaries. |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 17% |
| Austria | 1 | 17% |
| Norway | 1 | 17% |
| Unknown | 3 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 50% |
| Members of the public | 3 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 5% |
| Japan | 1 | 5% |
| Unknown | 20 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 32% |
| Student > Ph. D. Student | 5 | 23% |
| Student > Bachelor | 3 | 14% |
| Professor > Associate Professor | 3 | 14% |
| Student > Doctoral Student | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 2 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 9 | 41% |
| Biochemistry, Genetics and Molecular Biology | 4 | 18% |
| Computer Science | 3 | 14% |
| Immunology and Microbiology | 1 | 5% |
| Earth and Planetary Sciences | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 3 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 28 May 2014.
All research outputs
#6,923,553
of 23,344,526 outputs
Outputs from BMC Bioinformatics
#2,617
of 7,387 outputs
Outputs of similar age
#65,589
of 228,706 outputs
Outputs of similar age from BMC Bioinformatics
#49
of 149 outputs
Altmetric has tracked 23,344,526 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 7,387 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 gotten more attention than average, scoring higher than 64% 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 228,706 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 149 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.