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| Chapter title |
Meta-analysis of Cancer Gene Profiling Data.
|
|---|---|
| Chapter number | 12 |
| Book title |
Cancer Gene Profiling
|
| Published in |
Methods in molecular biology, January 2016
|
| DOI | 10.1007/978-1-4939-3204-7_12 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-3203-0, 978-1-4939-3204-7
|
| Authors |
Janine Roy, Christof Winter, Michael Schroeder |
| Editors |
Robert Grützmann, Christian Pilarsky |
| Abstract |
The simultaneous measurement of thousands of genes gives the opportunity to personalize and improve cancer therapy. In addition, the integration of meta-data such as protein-protein interaction (PPI) information into the analyses helps in the identification and prioritization of genes from these screens.Here, we describe a computational approach that identifies genes prognostic for outcome by combining gene profiling data from any source with a network of known relationships between genes. |
Mendeley readers
The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 8% |
| Unknown | 11 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 33% |
| Lecturer | 2 | 17% |
| Student > Doctoral Student | 2 | 17% |
| Librarian | 1 | 8% |
| Student > Ph. D. Student | 1 | 8% |
| Other | 1 | 8% |
| Unknown | 1 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 3 | 25% |
| Medicine and Dentistry | 3 | 25% |
| Agricultural and Biological Sciences | 2 | 17% |
| Computer Science | 2 | 17% |
| Unknown | 2 | 17% |