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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Maximum predictive power of the microarray-based models for clinical outcomes is limited by correlation between endpoint and gene expression profile
|
|---|---|
| Published in |
BMC Genomics, December 2011
|
| DOI | 10.1186/1471-2164-12-s5-s3 |
| Pubmed ID | |
| Authors |
Chen Zhao, Leming Shi, Weida Tong, John D Shaughnessy, André Oberthuer, Lajos Pusztai, Youping Deng, W Fraser Symmans, Tieliu Shi |
| Abstract |
Microarray data have been used for gene signature selection to predict clinical outcomes. Many studies have attempted to identify factors that affect models' performance with only little success. Fine-tuning of model parameters and optimizing each step of the modeling process often results in over-fitting problems without improving performance. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
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% |
| Denmark | 1 | 5% |
| Romania | 1 | 5% |
| Unknown | 19 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 10 | 45% |
| Student > Ph. D. Student | 3 | 14% |
| Lecturer > Senior Lecturer | 1 | 5% |
| Other | 1 | 5% |
| Professor > Associate Professor | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 5 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 6 | 27% |
| Psychology | 3 | 14% |
| Medicine and Dentistry | 3 | 14% |
| Computer Science | 2 | 9% |
| Biochemistry, Genetics and Molecular Biology | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 6 | 27% |
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 08 March 2012.
All research outputs
#18,305,470
of 22,663,969 outputs
Outputs from BMC Genomics
#8,144
of 10,613 outputs
Outputs of similar age
#195,529
of 243,187 outputs
Outputs of similar age from BMC Genomics
#224
of 298 outputs
Altmetric has tracked 22,663,969 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,613 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 12th percentile – i.e., 12% 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 243,187 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 298 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.