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X Demographics
Mendeley readers
Attention Score in Context
| Title |
New network topology approaches reveal differential correlation patterns in breast cancer
|
|---|---|
| Published in |
BMC Systems Biology, August 2013
|
| DOI | 10.1186/1752-0509-7-78 |
| Pubmed ID | |
| Authors |
Michael Bockmayr, Frederick Klauschen, Balazs Györffy, Carsten Denkert, Jan Budczies |
| Abstract |
Analysis of genome-wide data is often carried out using standard methods such as differential expression analysis, clustering analysis and heatmaps. Beyond that, differential correlation analysis was suggested to identify changes in the correlation patterns between disease states. The detection of differential correlation is a demanding task, as the number of entries in the gene-by-gene correlation matrix is large. Currently, there is no gold standard for the detection of differential correlation and statistical validation. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 3 | 5% |
| Iran, Islamic Republic of | 1 | 2% |
| United States | 1 | 2% |
| Germany | 1 | 2% |
| Unknown | 53 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 18 | 31% |
| Student > Ph. D. Student | 15 | 25% |
| Student > Bachelor | 6 | 10% |
| Other | 4 | 7% |
| Student > Postgraduate | 4 | 7% |
| Other | 9 | 15% |
| Unknown | 3 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 20 | 34% |
| Computer Science | 13 | 22% |
| Biochemistry, Genetics and Molecular Biology | 8 | 14% |
| Mathematics | 4 | 7% |
| Medicine and Dentistry | 4 | 7% |
| Other | 5 | 8% |
| Unknown | 5 | 8% |
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 13 November 2013.
All research outputs
#15,279,577
of 22,721,584 outputs
Outputs from BMC Systems Biology
#644
of 1,142 outputs
Outputs of similar age
#120,929
of 196,024 outputs
Outputs of similar age from BMC Systems Biology
#9
of 21 outputs
Altmetric has tracked 22,721,584 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 1,142 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 32nd percentile – i.e., 32% 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 196,024 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 21 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 57% of its contemporaries.