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Presented by S. Ravichandran, Ph.D., BIDS, Frederick National Laboratory for Cancer Research (FNLCR)

This document will explain how to use genomic expression data for classifying different cancer/tumor sites/types. This workshop is a follow-up to the NCI-DOE Pilot1 benchmark also called TC1. You can read about the project here, https://github.com/ECP-CANDLE/Benchmarks/tree/master/Pilot1/TC1

To begin:

• Click the launch Binder button below to begin tutorial using the dynamic versions of TC1-dataprep.ipynb and TC1-ConvNN.ipynb

  

• Please note that Binder server setup on the cloud will take < 3 minutes at most. You will first see a Binder page with some log messages. After the setup, you will see an instance of Jupyer notebook in your browser. Click the Jupyter notebook, predict-drugclass.ipynb, to begin the tutorial.

• Binder does not work with Safari on Mac OS, instead use the Chrome browser. If you are on Windows, please use Chrome.

• If you have trouble with Binder, click either TC1-dataprep.ipynb or TC1-ConvNN.ipynb above to view a static Python JupyterNotebook.