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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Profiling the human response to physical exercise: a computational strategy for the identification and kinetic analysis of metabolic biomarkers
|
|---|---|
| Published in |
Journal of Clinical Bioinformatics, December 2011
|
| DOI | 10.1186/2043-9113-1-34 |
| Pubmed ID | |
| Authors |
Michael Netzer, Klaus M Weinberger, Michael Handler, Michael Seger, Xiaocong Fang, Karl G Kugler, Armin Graber, Christian Baumgartner |
| Abstract |
In metabolomics, biomarker discovery is a highly data driven process and requires sophisticated computational methods for the search and prioritization of novel and unforeseen biomarkers in data, typically gathered in preclinical or clinical studies. In particular, the discovery of biomarker candidates from longitudinal cohort studies is crucial for kinetic analysis to better understand complex metabolic processes in the organism during physical activity. |
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 % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 2% |
| Germany | 1 | 2% |
| Switzerland | 1 | 2% |
| Unknown | 38 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 11 | 27% |
| Student > Master | 7 | 17% |
| Student > Ph. D. Student | 6 | 15% |
| Student > Doctoral Student | 2 | 5% |
| Student > Postgraduate | 2 | 5% |
| Other | 6 | 15% |
| Unknown | 7 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 11 | 27% |
| Medicine and Dentistry | 5 | 12% |
| Computer Science | 5 | 12% |
| Biochemistry, Genetics and Molecular Biology | 3 | 7% |
| Chemistry | 2 | 5% |
| Other | 6 | 15% |
| Unknown | 9 | 22% |
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 19 December 2011.
All research outputs
#20,674,485
of 25,394,764 outputs
Outputs from Journal of Clinical Bioinformatics
#44
of 61 outputs
Outputs of similar age
#203,336
of 248,852 outputs
Outputs of similar age from Journal of Clinical Bioinformatics
#6
of 9 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 61 research outputs from this source. They receive a mean Attention Score of 3.1. This one is in the 3rd percentile – i.e., 3% 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 248,852 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 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.