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Mendeley readers
Attention Score in Context
| Title |
Proteinortho: Detection of (Co-)orthologs in large-scale analysis
|
|---|---|
| Published in |
BMC Bioinformatics, April 2011
|
| DOI | 10.1186/1471-2105-12-124 |
| Pubmed ID | |
| Authors |
Marcus Lechner, Sven Findeiß, Lydia Steiner, Manja Marz, Peter F Stadler, Sonja J Prohaska |
| Abstract |
Orthology analysis is an important part of data analysis in many areas of bioinformatics such as comparative genomics and molecular phylogenetics. The ever-increasing flood of sequence data, and hence the rapidly increasing number of genomes that can be compared simultaneously, calls for efficient software tools as brute-force approaches with quadratic memory requirements become infeasible in practise. The rapid pace at which new data become available, furthermore, makes it desirable to compute genome-wide orthology relations for a given dataset rather than relying on relations listed in databases. |
Mendeley readers
The data shown below were compiled from readership statistics for 552 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 5 | <1% |
| United States | 4 | <1% |
| Spain | 4 | <1% |
| Australia | 3 | <1% |
| United Kingdom | 2 | <1% |
| Sweden | 1 | <1% |
| South Africa | 1 | <1% |
| Brazil | 1 | <1% |
| Colombia | 1 | <1% |
| Other | 3 | <1% |
| Unknown | 527 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 143 | 26% |
| Student > Master | 93 | 17% |
| Researcher | 90 | 16% |
| Student > Bachelor | 59 | 11% |
| Student > Doctoral Student | 25 | 5% |
| Other | 61 | 11% |
| Unknown | 81 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 219 | 40% |
| Biochemistry, Genetics and Molecular Biology | 135 | 24% |
| Immunology and Microbiology | 18 | 3% |
| Computer Science | 17 | 3% |
| Environmental Science | 13 | 2% |
| Other | 39 | 7% |
| Unknown | 111 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 07 April 2018.
All research outputs
#7,576,904
of 23,106,390 outputs
Outputs from BMC Bioinformatics
#3,050
of 7,330 outputs
Outputs of similar age
#40,740
of 110,938 outputs
Outputs of similar age from BMC Bioinformatics
#29
of 66 outputs
Altmetric has tracked 23,106,390 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,330 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 gotten more attention than average, scoring higher than 50% 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 110,938 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 66 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.