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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A detailed error analysis of 13 kernel methods for protein-protein interaction extraction
|
|---|---|
| Published in |
BMC Bioinformatics, January 2013
|
| DOI | 10.1186/1471-2105-14-12 |
| Pubmed ID | |
| Authors |
Domonkos Tikk, Illés Solt, Philippe Thomas, Ulf Leser |
| Abstract |
Kernel-based classification is the current state-of-the-art for extracting pairs of interacting proteins (PPIs) from free text. Various proposals have been put forward, which diverge especially in the specific kernel function, the type of input representation, and the feature sets. These proposals are regularly compared to each other regarding their overall performance on different gold standard corpora, but little is known about their respective performance on the instance level. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Norway | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Hungary | 1 | 3% |
| Germany | 1 | 3% |
| Netherlands | 1 | 3% |
| France | 1 | 3% |
| Spain | 1 | 3% |
| United States | 1 | 3% |
| Unknown | 32 | 84% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 26% |
| Student > Master | 6 | 16% |
| Researcher | 5 | 13% |
| Student > Doctoral Student | 4 | 11% |
| Professor > Associate Professor | 3 | 8% |
| Other | 5 | 13% |
| Unknown | 5 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 21 | 55% |
| Agricultural and Biological Sciences | 5 | 13% |
| Biochemistry, Genetics and Molecular Biology | 4 | 11% |
| Medicine and Dentistry | 1 | 3% |
| Chemistry | 1 | 3% |
| Other | 0 | 0% |
| Unknown | 6 | 16% |
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 16 January 2013.
All research outputs
#20,178,948
of 22,693,205 outputs
Outputs from BMC Bioinformatics
#6,827
of 7,254 outputs
Outputs of similar age
#252,238
of 284,977 outputs
Outputs of similar age from BMC Bioinformatics
#128
of 139 outputs
Altmetric has tracked 22,693,205 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,254 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 1st percentile – i.e., 1% 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 284,977 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 139 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.