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Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 73–96 of 500 filtered models
370M-parameter ligand-conditioned discrete diffusion model that co-designs protein sequence and structure under explicit small-molecule constraints.
Protein complex structure prediction from amino acid sequence, deployed as a self-hosted SageMaker endpoint that returns mmCIF and ipTM confidence.
Protein language model conditioned on ensembles of computed conformations, giving state-aware embeddings for interaction, localization, and function.
Generative biological foundation model placing DNA, RNA, and protein in one shared vocabulary, spanning genomic, proteomic, and cross-molecule tasks.
Protein conformational ensemble generation guided by experimental observables, steering a pretrained diffusion sampler toward Boltzmann statistics.
Diffusion model that locates zinc binding sites in protein structures at 94% precision, without needing the number of ions specified.
Unified 100-billion-parameter protein language model combining autoencoding and autoregressive objectives for protein understanding and generation.
Graph transformer that scores the accuracy of predicted protein complex structures, ranking model pools using pairwise structural similarity graphs.
Protein-protein docking model adapting AlphaFold-Multimer with a docking module and flow-matching training to assemble subunits without MSAs.
Scoring function for protein, nucleic acid, and small-molecule complexes that predicts binding affinity, ranks docked poses, and screens ligands.
Reasoning-guided foundation model for de novo antibody CDR design, pairing a multimodal LLM understanding expert with a Boltz-1 diffusion expert.
De novo protein design from natural language: a 16B-parameter framework turning text descriptions into sequences via structure-conditioned generation.
Structure-conditioned protein sequence design, pairing a three-track architecture with discrete flow matching for fast, few-step inverse folding.
Protein structure accuracy estimation predicting a global TM-score from an equivariant graph network over residue geometry and Rosetta energy terms.
Remote-homolog template recognition that threads a sequence against clustered PDB and AlphaFold DB structures to improve AlphaFold2 modelling.
Multimodal protein language model extending ESM-2 and SaProt with a Structure Adapter over residue torsion angles for protein function prediction.
Protein language model that tokenizes sequence, backbone structure, and text into one vocabulary for function prediction, design, and fold editing.
Immune protein structure prediction for TCRs, antibodies, and nanobodies. Adapts ESMFold with LoRA, reaching 1.31 Å RMSD on the CDR3-beta loop.
DNA- and RNA-binding residue prediction from a nucleic-acid-adapted protein language model and an equivariant graph network over protein structure.
Unified drug design engine for protein-ligand structure prediction, binding affinity estimation, and compound generation from Isomorphic Labs.
Diffusion model for structure-based drug design that jointly generates 3D ligands and holo pocket conformations from an apo protein structure.
Machine-learned interatomic potential supplying quantum-quality geometric restraints for refining cryo-EM and X-ray protein structures in Phenix.