Name
Abstract | ||
|---|---|---|
Predictions based on proteins from the in-vitro derived networks significantly outperformed predictions based on known cancer genes indicating that Multi-Task learning can indeed identify accurate drug response networks. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1186/s12918-017-0471-8 | BMC Systems Biology |
Keywords | Field | DocType |
LINCS,Machine learning,TCGA | Clinical tests,Multi-task learning,Biology,Systems biology,Bioinformatics,Cancer | Journal |
Volume | Issue | Citations |
11 | 1 | 1 |
PageRank | References | Authors |
0.36 | 24 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Matthew Ruffalo | 1 | 1 | 1.04 |
| Petar Stojanov | 2 | 1 | 1.71 |
| Venkata Krishna Pillutla | 3 | 1 | 0.36 |
| rohan varma | 4 | 139 | 7.32 |
| Ziv Bar-Joseph | 5 | 1207 | 112.00 |