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Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 1009–1032 of 1102 filtered models
Full-precision LoRA fine-tuning of ESM-2 for per-residue binding site prediction, where low-rank constraints curb overfitting on small datasets.
4-bit QLoRA fine-tunes of ESM-2 for per-residue protein binding site prediction, released as a checkpoint family spanning 8M to 650M parameters.
Diffusion model for programmable protein design that jointly samples structures and sequences, conditioned on symmetry, shape, or text prompts.
Protein language models from 151M to 6.4B parameters, trained on over a billion sequences for sequence generation and zero-shot fitness prediction.
Protein motif-scaffolding driven by a protein language model instead of MSA pretraining, solving 22 of 24 benchmark problems with diverse backbones.
Encoder-decoder framework unifying molecules, proteins, and natural language with SELFIES notation for cross-modal drug discovery tasks.
Conditional GAN that generates small molecules against a protein-protein interaction interface, encoding the complex with graph attention networks.
MSA-free protein structure prediction that replaces multiple sequence alignments with a protein language model pre-trained on billions of sequences.
De novo protein backbone generation by SE(3) flow matching, with motif-scaffolding built in. Samples a designable backbone in seconds on one GPU.
Multitask peptide model predicting strain-specific minimum inhibitory concentrations against 34 bacteria directly from an amino acid sequence.
Structure-aware protein language model pairing amino acid tokens with Foldseek 3Di structural states, outperforming ESM-2 across 10 downstream tasks.
Interface residue accuracy estimation for protein complexes, predicting per-residue lDDT from whole-complex, per-monomer and cross-chain features.
Missense variant pathogenicity predictor built on AlphaFold 2 representations, scoring variants across the human proteome at 0.940 AuROC on ClinVar.
Codon-vocabulary protein language model that converts ProtBERT to 64 codon tokens via embedding seeding, masked pretraining, and distillation.
Discrete diffusion model for protein sequence and MSA generation, enabling controllable de novo design directly in sequence space without structure.
Multimodal biomedical language model that answers free-text questions about molecular graphs and protein sequences as well as literature.
Antibody CDR design framework pairing a pretrained antibody language model with a hierarchical graph neural network for one-shot CDR generation.
Protein language model ranking stabilizing mutations with no assay data, trained jointly to predict the growth temperature of each sequence's host.
Unsupervised transformer language model for TCR-epitope binding prediction that generalizes to unseen epitopes without needing negative examples.
Structure-conditioned graph transformer trained with masked language modeling to learn residue encodings for inverse folding and antibody design.
De novo protein design diffusion model that generates backbone structures conditioned on binding targets, symmetry constraints, and functional motifs.
Multimodal protein foundation model spanning sequence, structure, function, and evolution, used for de novo design and structure prediction.
De novo ligand design from a target protein sequence, writing SMILES autoregressively over a merged protein-ligand BPE vocabulary.