Code used to train models and produce input files for "Predicting fungal secondary metabolite activity from biosynthetic gene cluster data using machine learning" (Riedling et al. 2023).

The Jupyter notebooks fungal_only_trained_model and NP_prediction_bacterial_and_fungal contain the code necessary to train the models. The Jupyter notebooks titled Running_predictions contain the code to make predictions on SM bioactivity from antiSMASH and RGI input. The Jupyter notebooks require the additional Python scripts so keep all scripts in the same directory as the notebooks. The scripts to extract the features from the antiSMASH and RGI files are included in the notebooks.