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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Coral: an integrated suite of visualizations for comparing clusterings
|
|---|---|
| Published in |
BMC Bioinformatics, October 2012
|
| DOI | 10.1186/1471-2105-13-276 |
| Pubmed ID | |
| Authors |
Darya Filippova, Aashish Gadani, Carl Kingsford |
| Abstract |
Clustering has become a standard analysis for many types of biological data (e.g interaction networks, gene expression, metagenomic abundance). In practice, it is possible to obtain a large number of contradictory clusterings by varying which clustering algorithm is used, which data attributes are considered, how algorithmic parameters are set, and which near-optimal clusterings are chosen. It is a difficult task to sift though such a large collection of varied clusterings to determine which clustering features are affected by parameter settings or are artifacts of particular algorithms and which represent meaningful patterns. Knowing which items are often clustered together helps to improve our understanding of the underlying data and to increase our confidence about generated modules. |
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 % |
|---|---|---|
| France | 2 | 67% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 11% |
| Germany | 1 | 2% |
| Sweden | 1 | 2% |
| Brazil | 1 | 2% |
| Argentina | 1 | 2% |
| Luxembourg | 1 | 2% |
| Unknown | 42 | 79% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 18 | 34% |
| Student > Ph. D. Student | 11 | 21% |
| Student > Doctoral Student | 5 | 9% |
| Other | 5 | 9% |
| Student > Bachelor | 4 | 8% |
| Other | 9 | 17% |
| Unknown | 1 | 2% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 24 | 45% |
| Computer Science | 12 | 23% |
| Biochemistry, Genetics and Molecular Biology | 6 | 11% |
| Mathematics | 3 | 6% |
| Arts and Humanities | 2 | 4% |
| Other | 5 | 9% |
| Unknown | 1 | 2% |
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 12 November 2012.
All research outputs
#13,370,975
of 22,684,168 outputs
Outputs from BMC Bioinformatics
#4,190
of 7,253 outputs
Outputs of similar age
#100,229
of 183,628 outputs
Outputs of similar age from BMC Bioinformatics
#58
of 108 outputs
Altmetric has tracked 22,684,168 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,253 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 38th percentile – i.e., 38% 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 183,628 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 108 others from the same source and published within six weeks on either side of this one. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.