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X Demographics
Mendeley readers
Attention Score in Context
| Title |
An online database for the detection of novel archaeal sequences in human ESTs
|
|---|---|
| Published in |
Bioinformatics, April 2004
|
| DOI | 10.1093/bioinformatics/bth249 |
| Pubmed ID | |
| Authors |
Neil F. W. Saunders, Paul M. G. Curmi, Ricardo Cavicchioli |
| Abstract |
We have developed a rapid, automated screening system and online database to detect foreign sequences of archaeal origin in human expressed sequence tags. The aim of the screening is to detect transcripts that may be derived from novel, putative archaeal pathogens or symbionts. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 8% |
| Norway | 1 | 8% |
| Unknown | 10 | 83% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 42% |
| Professor | 3 | 25% |
| Student > Doctoral Student | 1 | 8% |
| Student > Ph. D. Student | 1 | 8% |
| Professor > Associate Professor | 1 | 8% |
| Other | 0 | 0% |
| Unknown | 1 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 7 | 58% |
| Biochemistry, Genetics and Molecular Biology | 1 | 8% |
| Computer Science | 1 | 8% |
| Medicine and Dentistry | 1 | 8% |
| Engineering | 1 | 8% |
| Other | 0 | 0% |
| Unknown | 1 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 21 July 2014.
All research outputs
#4,102,716
of 25,374,647 outputs
Outputs from Bioinformatics
#3,572
of 12,808 outputs
Outputs of similar age
#8,774
of 62,414 outputs
Outputs of similar age from Bioinformatics
#11
of 63 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,808 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has gotten more attention than average, scoring higher than 72% 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 62,414 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 85% of its contemporaries.
We're also able to compare this research output to 63 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.