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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Pattern search in BioPAX models
|
|---|---|
| Published in |
Bioinformatics, September 2013
|
| DOI | 10.1093/bioinformatics/btt539 |
| Pubmed ID | |
| Authors |
Özgün Babur, Bülent Arman Aksoy, Igor Rodchenkov, Selçuk Onur Sümer, Chris Sander, Emek Demir |
| Abstract |
BioPAX is a standard language for representing complex cellular processes, including metabolic networks, signal transduction and gene regulation. Owing to the inherent complexity of a BioPAX model, searching for a specific type of subnetwork can be non-trivial and difficult. |
X Demographics
The data shown below were collected from the profiles of 3 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 | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 67% |
| Members of the public | 1 | 33% |
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 Kingdom | 3 | 6% |
| Hungary | 1 | 2% |
| Ukraine | 1 | 2% |
| Spain | 1 | 2% |
| United States | 1 | 2% |
| Unknown | 42 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 17 | 35% |
| Student > Ph. D. Student | 10 | 20% |
| Student > Bachelor | 5 | 10% |
| Student > Postgraduate | 4 | 8% |
| Other | 3 | 6% |
| Other | 8 | 16% |
| Unknown | 2 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 16 | 33% |
| Agricultural and Biological Sciences | 14 | 29% |
| Computer Science | 13 | 27% |
| Medicine and Dentistry | 3 | 6% |
| Mathematics | 1 | 2% |
| Other | 0 | 0% |
| Unknown | 2 | 4% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 December 2013.
All research outputs
#16,046,765
of 25,371,288 outputs
Outputs from Bioinformatics
#9,768
of 12,808 outputs
Outputs of similar age
#113,962
of 199,095 outputs
Outputs of similar age from Bioinformatics
#151
of 196 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
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 is in the 20th percentile – i.e., 20% of its peers scored the same or lower than it.
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 199,095 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 196 others from the same source and published within six weeks on either side of this one. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.