TPpred-LE

The implementation of the paper TPpred-LE: Therapeutic peptide functions prediction based on label embedding

Requirements

The majoy dependencies used in this project are as following:

python  3.7
numpy 1.21.6
tqdm  4.64.1
pyyaml  6.0
scikit-learn  1.0.2
torch  1.11.0+cu113
tensorflow  1.14.0
tensorboardX  2.5.1
transformers  4.25.1

More detailed python libraries used in this project are referred to requirements.txt.

Generate the pssms by blast against NR database(https://ftp.ncbi.nlm.nih.gov/blast/db/). The features of the benchmark data are avilable at (http://bliulab.net/TPpred-LE/data/).
Create the features, logs, results directory in current path.
copy the pssm into features. It should be /features/pssm/xxx.pssm.
train and test the model: Train the model(Algorithm 1):

./train.sh

Retrain the model(Algorithm 2):

./retrain.sh

The (re)train_partial.sh is used to train with the limited datasets.

Name		Name	Last commit message	Last commit date
Latest commit History 14 Commits
data		data
datasets		datasets
models		models
trained_models		trained_models
utils		utils
README.md		README.md
config.yaml		config.yaml
dataset.py		dataset.py
main.py		main.py
requirement.txt		requirement.txt
retrain.sh		retrain.sh
retrain_partial.sh		retrain_partial.sh
run_network.py		run_network.py
train.sh		train.sh
train_partial.sh		train_partial.sh