|
| Status |
Public on Jan 01, 2013 |
| Title |
Prediction of Breast Cancer Estrogen Receptor Status using Machine Learning |
| Organism |
Homo sapiens |
| Experiment type |
Expression profiling by array
|
| Summary |
Gene expression profiles were generated from 199 primary breast cancer patients. Samples 1-176 were used in another study, GEO Series GSE22820, and form the training data set in this study. Sample numbers 200-222 form a validation set. This data is used to model a machine learning classifier for Estrogen Receptor Status.
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| |
|
| Overall design |
RNA was isolated from 199 primary breast cancer patients. A machine learning classifier was built to predict ER status using only three gene features.
|
| |
|
| Contributor(s) |
Graham K, Mackey J |
| Citation(s) |
24312637 |
| Submission date |
May 10, 2011 |
| Last update date |
Jan 23, 2019 |
| Contact name |
Kathryn Graham |
| Organization name |
University of Alberta
|
| Department |
Oncology
|
| Street address |
11560 University Ave
|
| City |
Edmonton |
| State/province |
Alberta |
| ZIP/Postal code |
T6G 1Z2 |
| Country |
Canada |
| |
|
| Platforms (1) |
| GPL6480 |
Agilent-014850 Whole Human Genome Microarray 4x44K G4112F (Probe Name version) |
|
| Samples (199)
|
|
| Relations |
| BioProject |
PRJNA140059 |
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