The aim of this GitHub repository is to allow you to reproduce the results and figures of the following study
Predicting rifampicin resistance in M. tuberculosis using machine learning informed by protein structural and chemical features
Charlotte I. Lynch, Dylan Adlard, Philip W Fowler
The above preprint has been submitted for peer-review and this README will be updated when the manuscript has been accepted for publication in a peer-reviewed journal.
The repository contains three main juypter notebooks: methods.ipynb, Results.ipynb, and Supplement.ipynb.
To install the Python dependencies, you can either use pip
$ pip install -r requirements.txt
or conda via
$ conda env create -f environment.yml
$ conda activate predict_rif_ml
The latter is preferable since it will install all the dependencies in an environment.