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X Demographics
Mendeley readers
Attention Score in Context
Title |
GOParGenPy: a high throughput method to generate Gene Ontology data matrices
|
---|---|
Published in |
BMC Bioinformatics, August 2013
|
DOI | 10.1186/1471-2105-14-242 |
Pubmed ID | |
Authors |
Ajay Anand Kumar, Liisa Holm, Petri Toronen |
X Demographics
The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 3 | 30% |
United States | 2 | 20% |
Germany | 1 | 10% |
Canada | 1 | 10% |
Belgium | 1 | 10% |
Unknown | 2 | 20% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 5 | 50% |
Members of the public | 5 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | 6% |
Brazil | 3 | 6% |
United Kingdom | 2 | 4% |
Italy | 1 | 2% |
Netherlands | 1 | 2% |
Ukraine | 1 | 2% |
Australia | 1 | 2% |
Unknown | 37 | 76% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 21 | 43% |
Student > Ph. D. Student | 8 | 16% |
Professor > Associate Professor | 5 | 10% |
Student > Doctoral Student | 4 | 8% |
Student > Bachelor | 3 | 6% |
Other | 5 | 10% |
Unknown | 3 | 6% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 19 | 39% |
Computer Science | 12 | 24% |
Biochemistry, Genetics and Molecular Biology | 11 | 22% |
Engineering | 3 | 6% |
Medicine and Dentistry | 1 | 2% |
Other | 0 | 0% |
Unknown | 3 | 6% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 03 March 2017.
All research outputs
#6,342,636
of 25,408,670 outputs
Outputs from BMC Bioinformatics
#2,122
of 7,701 outputs
Outputs of similar age
#49,979
of 209,026 outputs
Outputs of similar age from BMC Bioinformatics
#23
of 74 outputs
Altmetric has tracked 25,408,670 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 7,701 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 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 209,026 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 76% of its contemporaries.
We're also able to compare this research output to 74 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 70% of its contemporaries.