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Mendeley readers
| Title |
Improving gene expression data interpretation by finding latent factors that co-regulate gene modules with clinical factors
|
|---|---|
| Published in |
BMC Genomics, November 2011
|
| DOI | 10.1186/1471-2164-12-563 |
| Pubmed ID | |
| Authors |
Tianwei Yu, Yun Bai |
| Abstract |
In the analysis of high-throughput data with a clinical outcome, researchers mostly focus on genes/proteins that show first-order relations with the clinical outcome. While this approach yields biomarkers and biological mechanisms that are easily interpretable, it may miss information that is important to the understanding of disease mechanism and/or treatment response. Here we test the hypothesis that unobserved factors can be mobilized by the living system to coordinate the response to the clinical factors. |
Mendeley readers
The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 14% |
| France | 1 | 7% |
| Unknown | 11 | 79% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 50% |
| Professor > Associate Professor | 2 | 14% |
| Professor | 1 | 7% |
| Student > Ph. D. Student | 1 | 7% |
| Student > Bachelor | 1 | 7% |
| Other | 0 | 0% |
| Unknown | 2 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 5 | 36% |
| Medicine and Dentistry | 4 | 29% |
| Biochemistry, Genetics and Molecular Biology | 2 | 14% |
| Unknown | 3 | 21% |