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Mendeley readers
Attention Score in Context
| Title |
Iterative class discovery and feature selection using Minimal Spanning Trees
|
|---|---|
| Published in |
BMC Bioinformatics, September 2004
|
| DOI | 10.1186/1471-2105-5-126 |
| Pubmed ID | |
| Authors |
Sudhir Varma, Richard Simon |
| Abstract |
Clustering is one of the most commonly used methods for discovering hidden structure in microarray gene expression data. Most current methods for clustering samples are based on distance metrics utilizing all genes. This has the effect of obscuring clustering in samples that may be evident only when looking at a subset of genes, because noise from irrelevant genes dominates the signal from the relevant genes in the distance calculation. |
Mendeley readers
The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 3% |
| United States | 1 | 3% |
| Poland | 1 | 3% |
| Germany | 1 | 3% |
| Unknown | 28 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 31% |
| Researcher | 7 | 22% |
| Professor > Associate Professor | 4 | 13% |
| Student > Master | 2 | 6% |
| Professor | 1 | 3% |
| Other | 2 | 6% |
| Unknown | 6 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 10 | 31% |
| Agricultural and Biological Sciences | 7 | 22% |
| Biochemistry, Genetics and Molecular Biology | 2 | 6% |
| Social Sciences | 2 | 6% |
| Engineering | 2 | 6% |
| Other | 4 | 13% |
| Unknown | 5 | 16% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 07 July 2013.
All research outputs
#14,543,083
of 25,287,709 outputs
Outputs from BMC Bioinformatics
#4,007
of 7,672 outputs
Outputs of similar age
#62,186
of 69,906 outputs
Outputs of similar age from BMC Bioinformatics
#1
of 1 outputs
Altmetric has tracked 25,287,709 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,672 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 45th percentile – i.e., 45% 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 69,906 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them