ImmunoStruct (Nature Machine Intelligence 2025)
github.com/krishnaswamylab/immunostructMultimodal deep learning framework integrating peptide-MHC protein sequence, structure, and biochemical properties to predict class-I immunogenicity for infectious disease epitopes and cancer neoepitopes with cancer-wildtype contrastive learning, enabling personalized vaccine design (Krishnaswamy Lab, Yale University)
Sourced from
- Awesome AI for Science — github.com/krishnaswamylab/immunostruct
- GitHub — github.com/krishnaswamylab/immunostruct
Related resources
General-purpose deep learning backbone for molecular modeling
Learning the language of protein-protein interactions
Deep learning library for Chemistry based on Tensorflow
Trainable, memory-efficient PyTorch reproduction and retraining of AlphaFold2 providing new insights into its learning dynamics and out-of-distribution generalization; widely used as the open-source AlphaFold2 backbone underpinning many downstream protein structure prediction and design pipelines (Columbia AlQuraishi Lab & OpenFold Consortium, Nature Methods 2024)
Foundation AutoResearch Operating System: blueprint-driven runtime for orchestrating AI research workflows from idea generation and experiments to paper writing and peer review (OpenNSWM-Lab, 2.4K+ stars, 2026)
Trainable PyTorch reproduction of AlphaFold 3