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X Demographics
Mendeley readers
Attention Score in Context
| Title |
eHive: An Artificial Intelligence workflow system for genomic analysis
|
|---|---|
| Published in |
BMC Bioinformatics, May 2010
|
| DOI | 10.1186/1471-2105-11-240 |
| Pubmed ID | |
| Authors |
Jessica Severin, Kathryn Beal, Albert J Vilella, Stephen Fitzgerald, Michael Schuster, Leo Gordon, Abel Ureta-Vidal, Paul Flicek, Javier Herrero |
| Abstract |
The Ensembl project produces updates to its comparative genomics resources with each of its several releases per year. During each release cycle approximately two weeks are allocated to generate all the genomic alignments and the protein homology predictions. The number of calculations required for this task grows approximately quadratically with the number of species. We currently support 50 species in Ensembl and we expect the number to continue to grow in the future. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Sweden | 1 | 20% |
| India | 1 | 20% |
| United Kingdom | 1 | 20% |
| Canada | 1 | 20% |
| Unknown | 1 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 4 | 80% |
| Members of the public | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 104 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 4 | 4% |
| United States | 4 | 4% |
| Brazil | 2 | 2% |
| Spain | 2 | 2% |
| Australia | 1 | <1% |
| Canada | 1 | <1% |
| Sweden | 1 | <1% |
| Netherlands | 1 | <1% |
| Belgium | 1 | <1% |
| Other | 0 | 0% |
| Unknown | 87 | 84% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 33 | 32% |
| Student > Ph. D. Student | 13 | 13% |
| Student > Bachelor | 12 | 12% |
| Other | 9 | 9% |
| Student > Master | 9 | 9% |
| Other | 20 | 19% |
| Unknown | 8 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 53 | 51% |
| Computer Science | 16 | 15% |
| Biochemistry, Genetics and Molecular Biology | 9 | 9% |
| Medicine and Dentistry | 6 | 6% |
| Engineering | 3 | 3% |
| Other | 8 | 8% |
| Unknown | 9 | 9% |
Attention Score in Context
This research output has an Altmetric Attention Score of 16. 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 23 March 2017.
All research outputs
#1,894,575
of 22,651,245 outputs
Outputs from BMC Bioinformatics
#475
of 7,236 outputs
Outputs of similar age
#6,820
of 94,877 outputs
Outputs of similar age from BMC Bioinformatics
#3
of 69 outputs
Altmetric has tracked 22,651,245 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,236 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 particularly well, scoring higher than 93% 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 94,877 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 69 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.