ML-in-molecular-biology

Course topics

1. Mutational signatures in cancer as an example problem for the course using Non-negative matrix factorisation
2. Probabilistic modelling, mutational signatures continued from a probabilistic view point. Expectation Maximisation. Sparsity of models.
3. Clustering, Hidden Markov Models: cancer subclone reconstruction problem as an example.
4. Symbolic Regression and its applications in biology
5. Reinforcement Learning and its applications in biology
6. Deep learning in molecular biology
7. Predicting drug combination responses in cancer with machine learning
8. Machine Learning in metagenomics

Group work

Training multiple different models (using python scikit learn library) on mutational profiles and signature activities to predict cancer types.