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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Integrative prescreening in analysis of multiple cancer genomic studies
|
|---|---|
| Published in |
BMC Bioinformatics, July 2012
|
| DOI | 10.1186/1471-2105-13-168 |
| Pubmed ID | |
| Authors |
Rui Song, Jian Huang, Shuangge Ma |
| Abstract |
In high throughput cancer genomic studies, results from the analysis of single datasets often suffer from a lack of reproducibility because of small sample sizes. Integrative analysis can effectively pool and analyze multiple datasets and provides a cost effective way to improve reproducibility. In integrative analysis, simultaneously analyzing all genes profiled may incur high computational cost. A computationally affordable remedy is prescreening, which fits marginal models, can be conducted in a parallel manner, and has low computational cost. |
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 % |
|---|---|---|
| Germany | 1 | 50% |
| United States | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 5% |
| Sweden | 1 | 5% |
| Germany | 1 | 5% |
| Unknown | 19 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 9 | 41% |
| Student > Postgraduate | 3 | 14% |
| Student > Ph. D. Student | 3 | 14% |
| Student > Doctoral Student | 2 | 9% |
| Student > Bachelor | 2 | 9% |
| Other | 2 | 9% |
| Unknown | 1 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 10 | 45% |
| Medicine and Dentistry | 4 | 18% |
| Mathematics | 2 | 9% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 9% |
| Computer Science | 2 | 9% |
| Other | 1 | 5% |
| Unknown | 1 | 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 July 2012.
All research outputs
#14,147,730
of 22,671,366 outputs
Outputs from BMC Bioinformatics
#4,712
of 7,247 outputs
Outputs of similar age
#95,897
of 163,495 outputs
Outputs of similar age from BMC Bioinformatics
#53
of 93 outputs
Altmetric has tracked 22,671,366 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,247 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 30th percentile – i.e., 30% 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 163,495 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 93 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.