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X Demographics
Mendeley readers
Attention Score in Context
| Title |
MCAM: Multiple Clustering Analysis Methodology for Deriving Hypotheses and Insights from High-Throughput Proteomic Datasets
|
|---|---|
| Published in |
PLoS Computational Biology, July 2011
|
| DOI | 10.1371/journal.pcbi.1002119 |
| Pubmed ID | |
| Authors |
Kristen M. Naegle, Roy E. Welsch, Michael B. Yaffe, Forest M. White, Douglas A. Lauffenburger |
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 % |
|---|---|---|
| Spain | 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 109 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 8 | 7% |
| United Kingdom | 2 | 2% |
| India | 1 | <1% |
| Germany | 1 | <1% |
| France | 1 | <1% |
| Luxembourg | 1 | <1% |
| Unknown | 95 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 35 | 32% |
| Student > Ph. D. Student | 30 | 28% |
| Other | 7 | 6% |
| Professor > Associate Professor | 7 | 6% |
| Professor | 5 | 5% |
| Other | 20 | 18% |
| Unknown | 5 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 55 | 50% |
| Biochemistry, Genetics and Molecular Biology | 16 | 15% |
| Computer Science | 10 | 9% |
| Chemistry | 7 | 6% |
| Engineering | 6 | 6% |
| Other | 8 | 7% |
| Unknown | 7 | 6% |
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 24 February 2022.
All research outputs
#7,356,343
of 25,374,647 outputs
Outputs from PLoS Computational Biology
#4,995
of 8,960 outputs
Outputs of similar age
#39,827
of 130,224 outputs
Outputs of similar age from PLoS Computational Biology
#33
of 65 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 8,960 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one is in the 42nd percentile – i.e., 42% 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 130,224 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 67% of its contemporaries.
We're also able to compare this research output to 65 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.