PepGAN

PepGAN is activity-aware generative adversarial network for peptide sequence generation.

Details about PepGAN methodology can be found here

PepGAN employs part of the benchmarking platform Texygen for more information see

Usage

PepGAN demo run can be made using following command
```
python main.py -g pepgan -t real -d data/amp.txt
```
To run PepGAN on own sequences first you have to train activity predictor using own provided positive and negative samples. Links to the locations of both sets should be added into the ../PepGAN/activity_predictor/classifiertrain.py file. Then activity predictor training can start
```
python classifiertrain.py
```
After that link to the trained model (.json and .h5 files) should be added into the ../PepGAN/models/Pepgan/PepganReward.py file. Afterwards when running PepGAN link to the positive dataset which will be used for discriminator training also must be provided
```
python main.py -g pepgan -t real -d <positive dataset location>
```

Name		Name	Last commit message	Last commit date
Latest commit History 110 Commits
AMP_predictor		AMP_predictor
activity_predictor		activity_predictor
data		data
models		models
save		save
utils		utils
README.md		README.md
main.py		main.py
requirements.txt		requirements.txt