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Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 505–528 of 2565 models
DNA language model whose tokenizer partitions the genome by evolutionary conservation, keeping transcription factor motifs intact as single tokens.
Chromatin-informed foundation model predicting regulatory activity and chromatin state directly from plant genomic sequence in Arabidopsis and rice.
Viral protein annotation model predicting ten residue-level classes from sequence alone: topology, glycosylation, cleavage sites and disorder.
464M-parameter structure prediction and design model that improves antibody-antigen complex accuracy over Protenix-v1 and adds generative VHH design.
Multimodal diffusion model that co-designs protein sequence and 3D structure around cofactors and small molecules for de novo heme enzyme design.
Genomic foundation model that learns DNA representations by predicting masked regions in latent space rather than reconstructing raw nucleotides.
Whole-cell segmentation model for spatial transcriptomics that fuses DAPI nuclear images with RNA transcript density to recover true cell boundaries.
Graph transformer that decides whether two proteins interact by fusing atomic packing density, surface geometry and language-model embeddings.
Spatial transcriptomics foundation model pairing gene expression with H&E histology for spatial domain discovery and clinical outcome prediction.
Diffusion-transformer pathology model embedding H&E histology, RNA profiles, and clinical text in a latent space for zero-shot cross-modal synthesis.
Transformer that classifies tumour types and subtypes from somatic variants in whole-genome and whole-exome data, with auto-downloading checkpoints.
Hybrid framework that predicts ribosome location profiles from mRNA sequence alone, pairing a structure-aware TASEP simulation with a Mamba polisher.
Long-context plant DNA language model, 676M parameters on a Mamba2 backbone, pretrained on 65 angiosperm genomes for cross-species variant annotation.
Graph attention model that learns context-aware protein embeddings from protein-protein interaction, co-expression, and tissue association networks.
Flow cytometry foundation model that reads heterogeneous antibody panels through a universal marker embedding to predict sample-level phenotypes.
Neuro-symbolic inverse folding that turns a backbone into a Potts model and hands it to an automated-reasoning solver for constrained design.
Anti-phage defense gene predictor fusing protein language model embeddings with a contrastive genomic-context transformer over 64-gene windows.
Autoregressive model for therapeutic mRNA design that jointly generates 5' UTR, CDS, and 3' UTR, pretrained on 30 million full-length natural mRNAs.
Dephosphorylation site prediction from protein sequence, pairing a LoRA-adapted ProtT5 encoder with a metaheuristic-tuned convolutional head.
Discrete diffusion model that designs regulatory DNA with tunable cell-type-specific activity and learns activity-predictive representations.
Gastrointestinal histopathology foundation model pretrained on 353 million multi-scale patches from 210,000 H&E whole-slide images of GI tissue.
Single-cell foundation model combining regulatory network priors with a Mamba backbone for clustering, batch integration, and perturbation modeling.
Generative imaging model simulating single-cell fluorescence microscopy for all 12,800 human proteins in the Human Protein Atlas.