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Mendeley readers
Attention Score in Context
| Title |
RankAggreg, an R package for weighted rank aggregation
|
|---|---|
| Published in |
BMC Bioinformatics, February 2009
|
| DOI | 10.1186/1471-2105-10-62 |
| Pubmed ID | |
| Authors |
Vasyl Pihur, Susmita Datta, Somnath Datta |
| Abstract |
Researchers in the field of bioinformatics often face a challenge of combining several ordered lists in a proper and efficient manner. Rank aggregation techniques offer a general and flexible framework that allows one to objectively perform the necessary aggregation. With the rapid growth of high-throughput genomic and proteomic studies, the potential utility of rank aggregation in the context of meta-analysis becomes even more apparent. One of the major strengths of rank-based aggregation is the ability to combine lists coming from different sources and platforms, for example different microarray chips, which may or may not be directly comparable otherwise. |
Mendeley readers
The data shown below were compiled from readership statistics for 271 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 3 | 1% |
| France | 3 | 1% |
| United States | 3 | 1% |
| United Kingdom | 2 | <1% |
| Canada | 2 | <1% |
| Spain | 2 | <1% |
| Belgium | 2 | <1% |
| Sweden | 1 | <1% |
| Ukraine | 1 | <1% |
| Other | 8 | 3% |
| Unknown | 244 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 75 | 28% |
| Researcher | 54 | 20% |
| Student > Master | 40 | 15% |
| Student > Bachelor | 17 | 6% |
| Other | 14 | 5% |
| Other | 41 | 15% |
| Unknown | 30 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 79 | 29% |
| Computer Science | 46 | 17% |
| Engineering | 23 | 8% |
| Biochemistry, Genetics and Molecular Biology | 20 | 7% |
| Mathematics | 13 | 5% |
| Other | 49 | 18% |
| Unknown | 41 | 15% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 24 March 2022.
All research outputs
#3,641,305
of 23,400,864 outputs
Outputs from BMC Bioinformatics
#1,235
of 7,376 outputs
Outputs of similar age
#11,368
of 95,343 outputs
Outputs of similar age from BMC Bioinformatics
#7
of 55 outputs
Altmetric has tracked 23,400,864 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,376 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 done well, scoring higher than 82% 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 95,343 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 85% of its contemporaries.
We're also able to compare this research output to 55 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.