Setup

Requires Python 3.7 or newer.

# in repository root directory

virtualenv -p python3 venv
source venv/bin/activate
pip install -r requirements.txt

For the assignments dealing with protein surface, a molecular surface calculator library, used by BioPython, has to be installed. Go to http://mgltools.scripps.edu/downloads#msms and select your binary. On linux, I had to extract the archive and for BioPython to find it, I linked the binary to /usr/local/bin/msms (should be in PATH under msms).

sudo ln /path_to_extracted_archive/msms.x86_64Linux2.2.6.1 /usr/local/bin/msms

If you don't have jupyter notebook already installed you can install it for your Python, or for this virtualenv:

pip install notebook  # (run either in the venv or not)

Overview

The repository includes a Python package at /assignments. It contains the library functions as well as source code for all of the assignments.

Jupyter notebook /assignment_demos.ipynb contains solutions for all the assignments, shows that the required tasks are completed, comments on the solution and, if applicable, discusses the results.

The code in the notebook was compiled from the assignment solutions in the Python modules in /assignments. They are located in if __name__ == '__main__': blocks and also serve as example usage for the library functions in the module.

All assignments have their own package/module, except assignment 'Conservation determination from multiple aligned sequences', that functionality is included in /assignments/clustal_parser ('Processing multiple sequence alignment').

Third party Python libraries used include BioPython (+ non-Python msms, molecular surface calculator), rmsd (Kabsch algorithm) and plotting libraries (matplotlib, seaborn).

Run

Launch jupyter notebook and open assignment_demos.ipynb in the web interface

or check the examples at the end of the sources and run the modules. They import from other packages of this library (relative imports ), so you have to run the modules with respect to the root package (root of the Python library). In the virtual environment, run python -m assignments.path.to.module e.g. assignments.structure_related_properties.lib. Run this at the repository root level.

The 'frontend' for this library is Python (possibly iPython notebooks). It's a good scripting language already and writing just a wrapper for shell commandline execution doesn't make sense for me.