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Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 721–744 of 1004 filtered models
De novo cyclic peptide binder design against a protein target, chaining a cyclized diffusion sampler, sequence design and structure prediction.
Protein language model extending ESM-2 to 2,048-residue inputs with LongFormer-style local windowed attention, re-pretrained on Swiss-Prot.
Latent diffusion model for controllable all-atom protein generation that co-designs sequence and structure while training on sequences alone.
Int4 LoRA adapters over long-context ESM-2 checkpoints, cutting the 33-layer load footprint to 664 MB and adding a 36-layer configuration.
Pocket-conditioned 3D ligand generator built on rectified flow, reaching -8.50 average Vina Dock and 75.0% diversity on CrossDocked2020.
Protein language model family at 300M, 600M, and 6B parameters, purpose-built for representation learning and outperforming ESM-2 at smaller scale.
Instruction-tuned gene language model extending LLaMA-7B with merged DNA and protein BPE vocabularies to answer sequence tasks as chat prompts.
Mixture-of-experts protein language model scaling to 16 billion parameters, applied to variant effect prediction and de novo protein design.
Drug-target affinity prediction pairing an SE(3)-equivariant GNN over 3D protein structure with a molecular GNN and residue-atom cross-attention.
GPCR-peptide complex structure prediction conditioned on active or inactive receptor states, used to rank designed peptide agonists and antagonists.
Antimicrobial peptide optimization framework pairing a transformer VAE latent space with constrained Bayesian optimization against an MIC oracle.
TCR-antigen binding affinity prediction for unseen peptides, pairing an ESM-2-initialized receptor encoder with a peptide cross-attention module.
Protein conformational ensemble generator using SE(3) flow matching from a perturbed ESMFold prior, sampling MD-like dynamics from sequence alone.
Protein inverse folding for low-resource enzyme design, distilling a frozen protein language model into a structure encoder used alone at inference.
Target-conditioned peptide binder design model that samples hot-spot residues from an energy-based density, then extends fragments autoregressively.
Flexible protein-ligand docking that repacks the pocket side chains from the backbone and the ligand graph before a physics sampler places the ligand.
RNA-binding protein binding profiles predicted base by base across 800 bp windows, with an m6A signal channel that exposes methylation-RBP crosstalk.
Vector-based virtual screening model that co-embeds proteins and small molecules so a drug-target interaction reduces to a single dot product.
De novo peptide design across non-canonical amino acid space, using guided diffusion over receptor-ligand interfaces to reach D-amino acid chemistry.
Peptide identification for diaPASEF proteomics, scoring fragment coelution across retention time and ion mobility with a pretrained CNN.
Protein-protein interaction prediction from structure alone, embedding each protein once so a proteome-wide dot product replaces pairwise queries.
Hydration-site prediction placing water molecules on protein surfaces by score-based diffusion, within 0.3 Å of crystallographic positions.
Target-conditioned generative language model that designs drug-like SMILES from a protein sequence, tuned on regulator-approved drug-target pairs.