Tutorial for the Teach-Discover-Treat (TDT) Competition 2014 - Challenge 1: Anti-Malaria hit finding using classifier-fusion boosted predictive models
This tutorial is an Python notebook which is a web-based interative environment where code, text and plots can be combined and the code snippets can be executed (and modified) directly. IPython can be installed on Linux, Mac and Windows - please follow the instructions on http://ipython.org/install.html.
For Linux, the interactive IPython notebook can be started by typing ipython notebook --pylab=inline in the base directory with the TDT\ challenge\ tutorial.ipynb file.
Alternatively, we provide the tutorial as an HTML and PDF file.
The tutorial was tested for Red Hat Linux. The Python libraries used in the tutorial are also available for Mac and Windows. All libraries are open-source.
These Python libraries are available through pip, yum or apt-get:
- scipy
- numpy
- matplotlib
- aggdraw or cairo
- scikit-learn
The cheminformatics toolkit RDKit can be obtained from http://rdkit.org and installation instructions can be found here: http://code.google.com/p/rdkit/w/list