Course project for CS 273B and CS 229. The goal is to train a deep learning model that takes one of eight kinases and a potential inhibitor, and predicts whether or not the kinase will be inhibited

1. Download the dataset from https://www.kaggle.com/xiaotawkaggle/inhibitors/home
2. Unzip and rename to "data", place in the repo's base directory
3. Make sure your conda version is 4.3.34
4. Create a conda virtual environment https://conda.io/docs/user-guide/tasks/manage-environments.html
5. conda create -n myenv python=3.5.3
6. activate
7. sudo apt-get install -y libxrender-dev
8. pip install -r requirements.txt
9. conda install cython
10. conda install -c conda-forge mdtraj
11. Install rdkit https://www.rdkit.org/docs/Install.html sudo apt-get install python-rdkit librdkit1 rdkit-data
12. Install https://github.com/kundajelab/simdna
13. gpu=0 bash scripts/install_deepchem_conda.sh (gpu=1 for GPU support)
14. Move deepchem folder to base directory