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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Tissue Specific Electrochemical Fingerprinting
|
|---|---|
| Published in |
PLOS ONE, November 2012
|
| DOI | 10.1371/journal.pone.0049654 |
| Pubmed ID | |
| Authors |
Pavlina Sobrova, Lenka Vyslouzilova, Olga Stepankova, Marketa Ryvolova, Jiri Anyz, Libuse Trnkova, Vojtech Adam, Jaromir Hubalek, Rene Kizek |
| Abstract |
Proteomics and metalloproteomics are rapidly developing interdisciplinary fields providing enormous amounts of data to be classified, evaluated and interpreted. Approaches offered by bioinformatics and also by biostatistical data analysis and treatment are therefore of extreme interest. Numerous methods are now available as commercial or open source tools for data processing and modelling ready to support the analysis of various datasets. The analysis of scientific data remains a big challenge, because each new task sets its specific requirements and constraints that call for the design of a targeted data pre-processing approach. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 25% |
| Unknown | 3 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 1 | 6% |
| Unknown | 15 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 3 | 19% |
| Professor > Associate Professor | 3 | 19% |
| Student > Master | 3 | 19% |
| Professor | 2 | 13% |
| Student > Doctoral Student | 2 | 13% |
| Other | 1 | 6% |
| Unknown | 2 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 3 | 19% |
| Computer Science | 2 | 13% |
| Medicine and Dentistry | 2 | 13% |
| Business, Management and Accounting | 1 | 6% |
| Biochemistry, Genetics and Molecular Biology | 1 | 6% |
| Other | 4 | 25% |
| Unknown | 3 | 19% |
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 27 June 2013.
All research outputs
#12,864,199
of 22,685,926 outputs
Outputs from PLOS ONE
#100,214
of 193,650 outputs
Outputs of similar age
#150,407
of 276,025 outputs
Outputs of similar age from PLOS ONE
#2,104
of 4,703 outputs
Altmetric has tracked 22,685,926 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 193,650 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.0. This one is in the 47th percentile – i.e., 47% 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 276,025 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 4,703 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.