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X Demographics
Mendeley readers
Attention Score in Context
Title |
Application of text-mining for updating protein post-translational modification annotation in UniProtKB
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Published in |
BMC Bioinformatics, March 2013
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DOI | 10.1186/1471-2105-14-104 |
Pubmed ID | |
Authors |
Anne-Lise Veuthey, Alan Bridge, Julien Gobeill, Patrick Ruch, Johanna R McEntyre, Lydie Bougueleret, Ioannis Xenarios |
Abstract |
The annotation of protein post-translational modifications (PTMs) is an important task of UniProtKB curators and, with continuing improvements in experimental methodology, an ever greater number of articles are being published on this topic. To help curators cope with this growing body of information we have developed a system which extracts information from the scientific literature for the most frequently annotated PTMs in UniProtKB. |
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 % |
---|---|---|
India | 2 | 50% |
Japan | 1 | 25% |
Norway | 1 | 25% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 3 | 75% |
Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 65 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Spain | 2 | 3% |
France | 1 | 2% |
Germany | 1 | 2% |
South Africa | 1 | 2% |
Australia | 1 | 2% |
Unknown | 59 | 91% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 18 | 28% |
Student > Master | 8 | 12% |
Student > Ph. D. Student | 7 | 11% |
Student > Bachelor | 5 | 8% |
Professor > Associate Professor | 5 | 8% |
Other | 10 | 15% |
Unknown | 12 | 18% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 19 | 29% |
Biochemistry, Genetics and Molecular Biology | 12 | 18% |
Computer Science | 11 | 17% |
Engineering | 2 | 3% |
Medicine and Dentistry | 2 | 3% |
Other | 6 | 9% |
Unknown | 13 | 20% |
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 08 April 2013.
All research outputs
#7,501,669
of 23,577,761 outputs
Outputs from BMC Bioinformatics
#2,928
of 7,418 outputs
Outputs of similar age
#63,675
of 199,159 outputs
Outputs of similar age from BMC Bioinformatics
#61
of 145 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 7,418 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 58% 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 199,159 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 66% of its contemporaries.
We're also able to compare this research output to 145 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 55% of its contemporaries.