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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Gel2DE - A software tool for correlation analysis of 2D gel electrophoresis data
|
|---|---|
| Published in |
BMC Bioinformatics, July 2013
|
| DOI | 10.1186/1471-2105-14-215 |
| Pubmed ID | |
| Authors |
Ola Kristoffer Øye, Katarina M Jørgensen, Sigrun M Hjelle, André Sulen, Dag Magne Ulvang, Bjørn Tore Gjertsen |
| Abstract |
Two-dimensional gel electrophoresis (2DE) is a powerful technique for studying protein isoforms and their modifications. Existing commercial 2D image analysis tools rely on spot detection that limits analysis of complex protein profiles, e.g. spot appearance/disappearance or overlapping spots. Pixel-by-pixel correlation analysis, an analysis technique for identifying relations between protein patterns in gel images and external variables, can overcome such limitations in spot analysis. |
X Demographics
The data shown below were collected from the profiles of 3 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 Kingdom | 1 | 33% |
| Finland | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 67% |
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 3% |
| Unknown | 38 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 13 | 33% |
| Student > Ph. D. Student | 7 | 18% |
| Student > Bachelor | 4 | 10% |
| Student > Master | 4 | 10% |
| Professor > Associate Professor | 3 | 8% |
| Other | 3 | 8% |
| Unknown | 5 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 19 | 49% |
| Computer Science | 3 | 8% |
| Biochemistry, Genetics and Molecular Biology | 3 | 8% |
| Medicine and Dentistry | 2 | 5% |
| Engineering | 2 | 5% |
| Other | 5 | 13% |
| Unknown | 5 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 16 September 2015.
All research outputs
#6,334,755
of 23,881,329 outputs
Outputs from BMC Bioinformatics
#2,280
of 7,454 outputs
Outputs of similar age
#51,262
of 196,819 outputs
Outputs of similar age from BMC Bioinformatics
#31
of 91 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 7,454 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 69% of its peers.
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 196,819 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 73% of its contemporaries.
We're also able to compare this research output to 91 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 65% of its contemporaries.