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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Comparison of evolutionary algorithms in gene regulatory network model inference
|
|---|---|
| Published in |
BMC Bioinformatics, January 2010
|
| DOI | 10.1186/1471-2105-11-59 |
| Pubmed ID | |
| Authors |
Alina Sîrbu, Heather J Ruskin, Martin Crane |
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 % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 128 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 5% |
| Germany | 3 | 2% |
| Brazil | 3 | 2% |
| France | 2 | 2% |
| Italy | 1 | <1% |
| Austria | 1 | <1% |
| Turkey | 1 | <1% |
| Sweden | 1 | <1% |
| India | 1 | <1% |
| Other | 6 | 5% |
| Unknown | 103 | 80% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 37 | 29% |
| Researcher | 27 | 21% |
| Student > Master | 19 | 15% |
| Professor | 8 | 6% |
| Student > Bachelor | 8 | 6% |
| Other | 21 | 16% |
| Unknown | 8 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 42 | 33% |
| Agricultural and Biological Sciences | 38 | 30% |
| Biochemistry, Genetics and Molecular Biology | 12 | 9% |
| Engineering | 9 | 7% |
| Arts and Humanities | 2 | 2% |
| Other | 9 | 7% |
| Unknown | 16 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 2016.
All research outputs
#15,380,359
of 22,881,154 outputs
Outputs from BMC Bioinformatics
#5,385
of 7,298 outputs
Outputs of similar age
#134,805
of 165,061 outputs
Outputs of similar age from BMC Bioinformatics
#39
of 61 outputs
Altmetric has tracked 22,881,154 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,298 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 18th percentile – i.e., 18% 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 165,061 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 61 others from the same source and published within six weeks on either side of this one. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.