Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 1–2 of 2 filtered models
OmicsML
Single-cell transformer that treats cells as tokens and tissues as sentences, encoding cell-cell relationships with 100x faster inference than prior pre-trained models.
Helmholtz Munich / Technical University of Munich
Transformer foundation model pretrained on 110M single-cell and spatially resolved transcriptomics profiles, enabling spatial context prediction for dissociated cells.