Improved prediction of Torsion angles of RNA by leveraging large language models.
The script slurm_setup_env.sh contains the commands to set up a minimal Anaconda environment on a HPC with a Slurm workload manager, the CUDA 11.6 toolkit can be loaded with the module load... command that is commented out in the script. The script can be run as follows:
source slurm_setup_env.sh
The ./data folder has all the data required to train and test TorRNA.
main.py trains a model of TorRNA and saves model checkpoints in the ./checkpoints folder. We have provided the best TorRNA models in this folder.
compare_predictions.py tests TorRNA on the test set, and also gives the prediction errors for SPOT-RNA-1D and a random baseline method.
All the results in the manuscript were generated using the .ipynb files provided in this repository.