robioson / netpred

🧶 An interpretable model for secondary structure prediction

NETPRED

The source code for NETPRED (an interpretable model for secondary structure prediction) can be found in the netpred subdirectory. Notebooks to analyse the model's behaviour can be found in the notebooks directory.

Requirements

• Python 3.9+
• Poetry
• An internet connection to download dependencies and data files
• At least 16GB of RAM for training, and around 15GB of disk space for files and dependencies
• Tested on GNU/Linux; other platforms will probably work, but they may not.

Installing dependencies

• Navigate to this directory
• Run poetry install.

Using the software

• config.py can be edited to configure embedding, data sources, and so on
• Once you have created the Poetry environment, run make train to begin training. All data files will be downloaded and extracted automatically
• To browse the notebooks, run make analyse.