You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
A new unsupervised gene clustering algorithm based on the integration of biological knowledge into expression data
|
|---|---|
| Published in |
BMC Bioinformatics, February 2013
|
| DOI | 10.1186/1471-2105-14-42 |
| Pubmed ID | |
| Authors |
Marie Verbanck, Sébastien Lê, Jérôme Pagès |
| Abstract |
Gene clustering algorithms are massively used by biologists when analysing omics data. Classical gene clustering strategies are based on the use of expression data only, directly as in Heatmaps, or indirectly as in clustering based on coexpression networks for instance. However, the classical strategies may not be sufficient to bring out all potential relationships amongst genes. |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 1 | 17% |
| United Kingdom | 1 | 17% |
| Switzerland | 1 | 17% |
| Norway | 1 | 17% |
| Unknown | 2 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 67% |
| Scientists | 2 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 5% |
| United Kingdom | 1 | 1% |
| Russia | 1 | 1% |
| France | 1 | 1% |
| Unknown | 73 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 17 | 21% |
| Researcher | 16 | 20% |
| Other | 8 | 10% |
| Student > Bachelor | 7 | 9% |
| Student > Master | 6 | 8% |
| Other | 11 | 14% |
| Unknown | 15 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 22 | 28% |
| Biochemistry, Genetics and Molecular Biology | 15 | 19% |
| Computer Science | 14 | 18% |
| Engineering | 5 | 6% |
| Mathematics | 3 | 4% |
| Other | 5 | 6% |
| Unknown | 16 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 February 2013.
All research outputs
#7,179,818
of 22,694,633 outputs
Outputs from BMC Bioinformatics
#2,857
of 7,254 outputs
Outputs of similar age
#81,389
of 282,966 outputs
Outputs of similar age from BMC Bioinformatics
#61
of 137 outputs
Altmetric has tracked 22,694,633 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
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 has gotten more attention than average, scoring higher than 58% 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 282,966 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 137 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 53% of its contemporaries.