**Before using the script,please add prPred into into environment variables**
## WGAN.py
python split_fasta.py -i your fasta file
Synthetic protein feature samples based on generative adversarial networks
## For windows 10 or later
## CTST2.py
Effector-GAN uses the leave-one-out cross-validation (LOOCV) method based on K nearest neighbor algorithm (KNN; K=1) classifier to evaluate the optimal synthetic protein feature samples, which are used to augment the original positive training samples
**Download Ubuntu xx.x LTS from Microsoft Store**
cd ../../
cd mnt/x/xxxx/xxxx/
git clone git@github.com:Wangys-prog/prPred.git
cd mnt/x/xxxx/xxxx/prPred/
## **If you use prPred, please cite:**
(1) Wang Y, Wang P, Guo Y, et al. prPred: A Predictor to Identify Plant Resistance Proteins by Incorporating k-Spaced Amino Acid (Group) Pairs[J]. Frontiers in bioengineering and biotechnology, 2021, 8: 1593.