All Competitors

Pretrained antibody structure predictor that outputs full paired heavy/light 3D structures faster than protein language models generate embeddings.

Cross-species, multimodal foundation model of immunology and inflammation that harmonizes transcriptomics and histology into unified patient-level representations.

A masked language model for T-cell receptor and peptide-MHC interaction prediction using compositional pretraining and entropy-guided non-autoregressive decoding.

A fine-tuned scLDM variant trained on 14.5 million CD4+ T cells for counterfactual prediction of single-gene perturbation effects in immune cells.

Generative language model trained on 558 million antibody sequences for infilling-based design of CDR loops and full-length immunoglobulin sequences.

A BERT-based antibody language model pre-trained on 57M BCR sequences for paratope prediction and convergent antibody discovery.

Antibody-specific language model trained on the OAS database for restoring missing residues and generating high-quality sequence representations.