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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Functional characterization of breast cancer using pathway profiles
|
|---|---|
| Published in |
BMC Medical Genomics, July 2014
|
| DOI | 10.1186/1755-8794-7-45 |
| Pubmed ID | |
| Authors |
Feng Tian, Yajie Wang, Michael Seiler, Zhenjun Hu |
| Abstract |
The molecular characteristics of human diseases are often represented by a list of genes termed "signature genes". A significant challenge facing this approach is that of reproducibility: signatures developed on a set of patients may fail to perform well on different sets of patients. As diseases are resulted from perturbed cellular functions, irrespective of the particular genes that contribute to the function, it may be more appropriate to characterize diseases based on these perturbed cellular functions. |
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 % |
|---|---|---|
| Canada | 1 | 25% |
| Germany | 1 | 25% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 2% |
| Sweden | 1 | 2% |
| Germany | 1 | 2% |
| Unknown | 48 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 20% |
| Student > Bachelor | 9 | 18% |
| Researcher | 9 | 18% |
| Student > Master | 9 | 18% |
| Professor > Associate Professor | 3 | 6% |
| Other | 5 | 10% |
| Unknown | 6 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 17 | 33% |
| Biochemistry, Genetics and Molecular Biology | 14 | 27% |
| Medicine and Dentistry | 6 | 12% |
| Computer Science | 3 | 6% |
| Engineering | 2 | 4% |
| Other | 3 | 6% |
| Unknown | 6 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 July 2014.
All research outputs
#3,176,865
of 22,758,963 outputs
Outputs from BMC Medical Genomics
#140
of 1,222 outputs
Outputs of similar age
#33,122
of 228,570 outputs
Outputs of similar age from BMC Medical Genomics
#2
of 15 outputs
Altmetric has tracked 22,758,963 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,222 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 88% 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 228,570 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.