sametz / MDAnalysis_ML_workshop

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From biomolecular data to information - 2022 CCP5 Summer School, Durham

This repository contains all the materials for the MDAnalysis/Machine Learning tutorials that form part of the CCP5 Biomolecular Simulation Advance Course taking place on July 26-27th at Durham University.

Instructors

Matteo Degiacomi
Micaela Matta
Antonia Mey

Location

Durham University
Room: W414

W414 is on the fourth floor of the Geography ("West") building. Enter at the northeast corner of the building at 54.767675, -1.573041. We've been asked not to use the "staff" toilets near W414, but rather to use the facilities on the ground floor. I shall be putting up some signage.

Schedule

Day Session Materials
26th PM Introduction to the MDAnalysis package (Micaela Matta) MDA Part 1
26th PM MDAnalysis: advanced topics (Micaela Matta) MDA Part 2
27th AM Dimensionality reduction, part 1 (Antonia Mey) Dimensionality reduction 1
27th AM Dimensionality reduction, part 2 (Matteo Degiacomi) Dimensionality reduction 2
27th PM Data clustering (Antonia Mey) Clustering
27th PM Data classification (Matteo Degiacomi) Classification

Setting up your Python environment before the workshop

Instructions for setting up your environment to run this workshop locally are provided in INSTALL.md.

A full list of the required Python packages can be seen inside environment.yml.

As downloading and installing everything will take a little while, ideally you should follow these steps before the workshop starts. If you encounter any issues during installation, we can help!

Google Colab

If for any reason you cannot set up a local environment with all required packages, you can use Google Colab to run all workshop notebooks directly from your browser, no installation required.

Course pre-requisites

The course assumes that attendees have a working knowledge of Jupyter notebooks, Python (especially the NumPy library), and the bash shell.

License

The MDAnalysis logo and its derivatives are licensed under the Creative Commons Attribution-NoDerivs 3.0 Unported License.

The MDAnalysis material is licences under CC-BY 4.0 Creative Commons Licence

The ML material is licenced under CC-BY-SA 4.0.

Creative Commons Licence

See here for the details of the licence

Acknowledgements

Please see AUTHORS.md for a list of contributors to the workshop materials.

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