Machine learning methods for the prediction of pathology in protein mutations, as in the PMut predictor.
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Type Name Latest commit message Commit time
Failed to load latest commit information.


PyMut is a Python 3 module that fills the gap between machine learning and bioinformatics, providing methods that help in the prediction of pathology in protein mutations. Using PyMut you can compute features, train predictors, evaluate them, predict the pathology of mutations, select the best features...


We recommend using Anaconda, a free distribution of the SciPy stack. To install PyMut, follow these steps:

Download anaconda with Python 3.5 for your platform (Windows, Linux or OSX), and install (double-click in Windows), or run in Linux of OSX:

  1. Create an anaconda Python 3 environment (we will name it pymut), and activate the environment:

    conda create python=3 --name pymut

    source activate pymut

  2. Install PyMut:

    pip install pymut


Visit the PyMut tutorial to see a full example of usage of PyMut. In the tutorial we show how to:

  • Compute features that describe mutations and plot their distribution.
  • Train classifiers, evaluate them using cross-validation and plot their ROC curves.
  • Select the best features.
  • Train a pathology predictor.
  • Predict the pathology of mutations using our newly trained predictor.

Sample plots generated by PyMut