ImmunoStruct
ImmunoStruct enables multimodal deep learning for immunogenicity prediction
Instructions on preparing everything and running training/inference is provided on our official GitHub repository.
The multimodal datasets of IEDB, CEDAR and clinical validation are available at our huggingface dataset repo.
In short, the models can be downloaded using
hf download ChenLiu1996/ImmunoStruct --local-dir ./
If possible, we will try to provide better serving of the models, but no guarantee.
Model details
We open-sourced two pre-trained models in the paper:
- IEDB_model_seed1.pt
- CEDAR_model_seed2.pt
The former can be used to run inference on the IEDB dataset.
The latter can be used to run inference on the CEDAR dataset and the clinical validation dataset.
Citation
If you use ImmunoStruct in your research, please cite our paper:
BibTeX:
@article{givechian2026immunostruct,
title={ImmunoStruct enables multimodal deep learning for immunogenicity prediction},
author={Givechian, Kevin Bijan and Rocha, Jo{\~a}o Felipe and Liu, Chen and Yang, Edward and Tyagi, Sidharth and Greene, Kerrie and Ying, Rex and Caron, Etienne and Iwasaki, Akiko and Krishnaswamy, Smita},
journal={Nature Machine Intelligence},
volume={8},
pages={70--83},
year={2026},
publisher={Nature Publishing Group UK London}
}
Nature format:
Givechian, K.B., Rocha, J.F., Liu, C. et al. ImmunoStruct enables multimodal deep learning for immunogenicity prediction. Nat Mach Intell 8, 70–83 (2026). https://doi.org/10.1038/s42256-025-01163-y