Pep2TCR is a deep learning framework based on transfer learning and ensemble learning, designed for predicting CD4 TCR-peptide binding. It fills the gap of lacking CD4 TCR-specific prediction tools and offers researchers an accurate prediction tool.

Pep2TCR has been developed and maintained by LiuxsLab – LiuLab at the School of Life Science and Technology, ShanghaiTech University. If you find it helpful, please consider citing it.

We have also provided a GitHub repository at https://github.com/XSLiuLab/Pep2TCR for users to review the source code, as well as a Docker image at Docker Hub for convenient deployment.