Awesome
discrete Walk-Jump Sampling (dWJS)
This is the official open source repository for discrete Walk-Jump Sampling developed by ncfrey, djberenberg, kleinhenz, and saeedsaremi, from Prescient Design, a Genentech accelerator.
See our experimental results immunizing against ERBB2 here!
Setup
Assuming you have miniconda installed, clone the repository, navigate inside, and run:
./scripts/install.sh
Training
The entrypoint train
is the main driver for training and accepts parameters using Hydra syntax.
The available parameters for configuration can be found by running train
--help or by looking in the src/walkjump/hydra_config
directory
Sampling
The entrypoint sample
is the main driver for training and accepts parameters using Hydra syntax.
The available parameters for configuration can be found by running sample
--help or by looking in the src/walkjump/hydra_config
directory
Contributing
We welcome contributions. If you would like to submit pull requests, please make sure you base your pull requests off the latest version of the main
branch.
License
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at https://www.apache.org/licenses/LICENSE-2.0.
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
Citations
If you use the code and/or model, please cite:
@article{frey2023protein,
title={Protein Discovery with Discrete Walk-Jump Sampling},
author={Nathan C. Frey and Daniel Berenberg and Karina Zadorozhny and Joseph Kleinhenz and Julien Lafrance-Vanasse and Isidro Hotzel and Yan Wu and Stephen Ra and Richard Bonneau and Kyunghyun Cho and Andreas Loukas and Vladimir Gligorijevic and Saeed Saremi},
year={2023},
eprint={2306.12360},
archivePrefix={arXiv},
primaryClass={q-bio.BM}
}