This repository contains Jupyter Notebooks that can be used as training materials for understanding how the PDBe REST API works, and provides a number of examples of answering specific questions about PDB entries using the API.

Either use Binder to use the notebook:

Or

You will need to have Jupyter installed on your machine. For Linux/OSX machines, simply type:

pip3 install --upgrade pip
pip3 install jupyter

For Windows machines (optionally also for Linux/OSX) you can install Jupyter with Anaconda: https://www.anaconda.com/download/

If installing using Anaconda, there is no additional prerequisites. If installing using pip3, you will need to have Python3 on your machine, and of course pip3

From command line on Unix machine these would be the steps setting up everyone:

mkdir pdbe_jupyter
cd pdbe_jupyter
git clone https://github.com/PDBeurope/pdbe-api-training .
jupyter notebook

Jupyter Notebook will open a window in your browser, and you can select the specific notebooks you would like to view.

• Mihaly Varadi - Initial work - github
• John Berrisford - Additional notebooks - github
• Preeti Choudhary - Ligand interactions and predicted models notebooks - github
• Joseph Ellaway - Protein superposing notebooks - github

This project is licensed under the EMBL-EBI License - see the LICENSE.md file for details

• Thanks to the PDBe team for suggestions during creating these materials