Loading…
Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 601–624 of 1102 filtered models
Protein language model interpretability adapter that factors ESM2 and ProtBERT embeddings into named biochemical features plus a residual subspace.
Flexible protein-ligand docking and binding affinity prediction from an apo receptor structure and ligand SMILES, using an 8-layer pair transformer.
TCR-pMHC specificity prediction that folds frozen ESM-2 and AlphaFold2 representations into a three-body peptide-MHC-CDR3 energy tensor.
Machine-learned interatomic potential supplying quantum-quality geometric restraints for refining cryo-EM and X-ray protein structures in Phenix.
Protein binder design that inverts the frozen Boltz-1 all-atom predictor, targeting small molecules, nucleic acids, metals, and modified residues.
Sequence-based protein stability predictor estimating ddG for single and multi-point mutations while enforcing thermodynamic antisymmetry.
De novo protein design from natural language: a 16B-parameter framework turning text descriptions into sequences via structure-conditioned generation.
Protein function prediction fusing five Gene Ontology pipelines, two of them deep models over protein and DNA language model embeddings.
Sequence-only peptide toxicity prediction, pairing a fine-tuned ESM-2 backbone with a bidirectional LSTM and focal loss for rare toxic peptides.
Protein function prediction that assigns Gene Ontology terms from predicted 3D structure, ESM-2 embeddings, and cross-species network propagation.
Controllable protein sequence generation that conditions latent diffusion on physicochemical properties aligned to natural-language prompts.
Antimicrobial peptide platform whose GPT-style generator is conditioned on E. coli or S. aureus activity, then filtered for potency and hemolysis.
Structure-based drug design model pairing an autoregressive transformer for ligand graphs with a diffusion head for 3D binding-pose coordinates.
De novo binder design across small molecules, peptides, and antibodies from one geometric latent diffusion model over graphs of molecular blocks.
De novo peptide sequencing from mirror-protease mass spectra, reading paired complementary spectra to recover near-complete fragment ion coverage.
Antibody sequence generation model that samples paired human VH/VL chains, covering inpainting, inverse folding, and CDR grafting in one network.
Transferable coarse-grained force field for molecular dynamics of proteins, RNA, and lipids, built on the MACE equivariant graph architecture.
Diffusion model that locates zinc binding sites in protein structures at 94% precision, without needing the number of ions specified.
Protein language model pretrained on over nine billion sequences, giving residue embeddings and zero-shot single-site mutant scores from its logits.
GPCR peptide agonist screening with a graph neural network over AlphaFold-Multimer active-state complexes and interatomic contact graphs.
Chemical language model family for target-aware ligand generation, conditioning molecule design on protein embeddings from a companion protein model.