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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Mining breast cancer genes with a network based noise-tolerant approach
|
|---|---|
| Published in |
BMC Systems Biology, June 2013
|
| DOI | 10.1186/1752-0509-7-49 |
| Pubmed ID | |
| Authors |
Yaling Nie, Jingkai Yu |
| Abstract |
Mining novel breast cancer genes is an important task in breast cancer research. Many approaches prioritize candidate genes based on their similarity to known cancer genes, usually by integrating multiple data sources. However, different types of data often contain varying degrees of noise. For effective data integration, it's important to design methods that work robustly with respect to noise. |
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 % |
|---|---|---|
| Peru | 1 | 33% |
| United States | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 33% |
| Members of the public | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 5% |
| China | 1 | 3% |
| Germany | 1 | 3% |
| Unknown | 36 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 28% |
| Researcher | 10 | 25% |
| Student > Master | 6 | 15% |
| Student > Doctoral Student | 2 | 5% |
| Student > Bachelor | 2 | 5% |
| Other | 8 | 20% |
| Unknown | 1 | 3% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 13 | 33% |
| Computer Science | 12 | 30% |
| Biochemistry, Genetics and Molecular Biology | 5 | 13% |
| Engineering | 2 | 5% |
| Medicine and Dentistry | 2 | 5% |
| Other | 4 | 10% |
| Unknown | 2 | 5% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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
#15,557,505
of 23,881,329 outputs
Outputs from BMC Systems Biology
#601
of 1,126 outputs
Outputs of similar age
#119,668
of 198,875 outputs
Outputs of similar age from BMC Systems Biology
#9
of 22 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,126 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 43rd percentile – i.e., 43% 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 198,875 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 22 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 63% of its contemporaries.