A python package for the prediction of protein functions as GO terms to participate in the CAFA-5 competition.
The development and testing of the functionalities were made using python3.8, on a linux ─ubuntu 20.4─ environment.
(optional) Create a virtual environment to install the package.
$ mkdir -p venv && python3 -m venv ./venv && source venv/bin/activate
And install it.
$ python3 -m pip install .
Enter a subshell in the virtual environment with dependencies available:
$ source venv/bin/activate
and run python tasks from inside the subshell.
- Tutorial1: Working with proteins and and protein structures.
- Tutorial2: Computing GO terms on the training set.
- Tutorial3: Computing candidate GO terms for model training.
- Tutorial4: Order candidate terms by information accrued.
- Tutorial5: Creating a single model and benchmarking its accuracy.
- Tutorial6: Massive training of models.
- Tutorial7: Massive prediction of protein functions.