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In PBL-3, we try to help an oncologist friend who's woking on genomics data to cure cancer. Specifically, the scientist want to analyze gene expression data of breast cancer patients.
The scientist want us to help him in three perspectives:
- Visualize the data
- This is to find how the patients are groupped and also to find if there's any patient who's gene expression is atypical compared to the group
- Find interesting genes
- This is to discover genes that contributes the most to the clinical outcome.
- The scientist want to investigate our findings further. We cannot perform bio-medical experiments, so use Google about your findings to verify the genes you've found could be something interesting.
- Build an effective classifer of grades 1, 2, and 3 (grade and statge)
- This classifier will help to detect if a new patient will be of high risk (grade 3) or low risk (grade 1).
Submission
- Python notebook
- Individual submission
- Replaces the final exam (grading of the final exam will be 'relative')
- Due Dec 18 (class 1), Dec 20 (class 2)
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