Name
Abstract | ||
|---|---|---|
While the pipeline produced several possible interactions where increased survival is linked to normal or increased copy number of a given gene for patients treated with a given drug, no instance of low copy number or full deletion was linked to increased survival. The development of this pipeline shows a promising utility to identify possible beneficial gene-drug interactions that could improve patient survival and may illustrate some of the problems inherent in this kind of analysis on these data. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1186/s12859-016-1255-7 | BMC Bioinformatics |
Keywords | Field | DocType |
Gene-drug interaction,Survival,TCGA | Biological data,Disease,Survival rate,Biology,Copy-number variation,Glioma,Bioinformatics,Survival analysis,Genetics,Cancer,DNA microarray | Journal |
Volume | Issue | ISSN |
17 | 1 | 1471-2105 |
Citations | PageRank | References |
1 | 0.65 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| John Christian Givhan Spainhour | 1 | 3 | 1.74 |
| Peng Qiu | 2 | 47 | 6.73 |