
By combining LLMs for sequence embedding and graph represetations for structural representation, TCR complex stability is predicted and stability-enhancing mutations are predicted. Biochemical basis for predictions are extracted.
Scope of the project:
- open source datasets are cleaned and preprocessed,
- graph representation of proteins and protein complexes
- Clone the repo
git clone [https://github.com/LilianDenzler/TCR_Graphs.git](https://github.com/LilianDenzler/TCR_Graphs.git)
- create and activate environment
conda env create --file=tcrgraphs.yaml conda activate tcrgraphs
Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature
) - Commit your Changes (
git commit -m 'Add some AmazingFeature'
) - Push to the Branch (
git push origin feature/AmazingFeature
) - Open a Pull Request
Distributed under the MIT License. See LICENSE.txt
for more information.
Don't hesitate to reach out!
Lilian Denzler- [][https://linkedin.com/liliandenzler] - [email protected]