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X Demographics
Mendeley readers
Attention Score in Context
| Title |
MarVis: a tool for clustering and visualization of metabolic biomarkers
|
|---|---|
| Published in |
BMC Bioinformatics, March 2009
|
| DOI | 10.1186/1471-2105-10-92 |
| Pubmed ID | |
| Authors |
Alexander Kaever, Thomas Lingner, Kirstin Feussner, Cornelia Göbel, Ivo Feussner, Peter Meinicke |
| Abstract |
A central goal of experimental studies in systems biology is to identify meaningful markers that are hidden within a diffuse background of data originating from large-scale analytical intensity measurements as obtained from metabolomic experiments. Intensity-based clustering is an unsupervised approach to the identification of metabolic markers based on the grouping of similar intensity profiles. A major problem of this basic approach is that in general there is no prior information about an adequate number of biologically relevant clusters. |
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 % |
|---|---|---|
| Unknown | 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 65 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 4 | 6% |
| Colombia | 1 | 2% |
| Unknown | 60 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 15 | 23% |
| Student > Ph. D. Student | 15 | 23% |
| Student > Bachelor | 10 | 15% |
| Student > Doctoral Student | 4 | 6% |
| Professor > Associate Professor | 4 | 6% |
| Other | 9 | 14% |
| Unknown | 8 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 28 | 43% |
| Biochemistry, Genetics and Molecular Biology | 11 | 17% |
| Computer Science | 5 | 8% |
| Engineering | 3 | 5% |
| Immunology and Microbiology | 2 | 3% |
| Other | 6 | 9% |
| Unknown | 10 | 15% |
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 10 July 2012.
All research outputs
#15,246,403
of 22,669,724 outputs
Outputs from BMC Bioinformatics
#5,360
of 7,247 outputs
Outputs of similar age
#79,261
of 93,793 outputs
Outputs of similar age from BMC Bioinformatics
#31
of 34 outputs
Altmetric has tracked 22,669,724 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,247 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 18th percentile – i.e., 18% 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 93,793 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 34 others from the same source and published within six weeks on either side of this one. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.