Machine learning approach to understand the importance of novel binding energy features in CRISPR/Cas9 activity prediction
The classification and regression ML models are written in Jupyter Notebook, the best performing model as well as other models tested are included. Feature importance analysis and results are also included. Initial data cleaning, sequence feature extraction and analysis steps are retained for reference.
The input data can be obtained on request.
(Suggestions are welcome!)