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Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 505–528 of 1004 filtered models
Antibody CDR design model fusing diffusion with a GFlowNet objective so binding energy is optimized during training rather than by post-hoc RL.
Protein representation model adding global fold-similarity and local substructure signals to masked pretraining, reaching 79.2 long-range contact P@L.
T-cell epitope immunogenicity prediction that fuses MHC presentation, TCR binding, and activation data via adversarial multi-domain pretraining.
Structure-based drug design by diffusing medicinal-chemistry fragments into a binding pocket, yielding synthesizable, selective, drug-like molecules.
Ligand-aware protein language model that cross-attends SaProt embeddings to ligand SMILES, beating SaProt across six downstream benchmarks.
Deep mutational scanning score imputation across protein domains, pairing ESM-1v embeddings with EVE conservation and physicochemical features.
Encoder-decoder codon language model that reverse-translates a protein into species-specific coding sequences for synthetic mRNA design.
Structure-based drug design that schedules noise separately for 3D coordinates and 2D topology, reaching a 95.9% PoseBusters valid rate on CrossDock.
Unified atomic diffusion model for protein structure prediction and de novo antibody design, steered by epitope and target-structure constraints.
Pocket-conditioned 3D diffusion model for scaffold decoration, guided by evolutionary residue conservation and a protein-ligand interaction prior.
Protein model accuracy estimation for single chains and complexes, predicting per-residue lDDT, interface QS-score, and overall fold TM-score.
Anticancer protein prediction from sequence with a fine-tuned ESM-2 650M classifier; a BLAST hybrid raises validation AUC to 0.91.
Generative diffusion model that samples biomolecular conformational ensembles for proteins, RNA, and ligands in hours instead of millisecond-scale MD.
Physics-guided all-atom diffusion model for protein-ligand complex prediction, reaching 95.3% success on PoseBusters redocking with a known pocket.
Peptide-MHC structure prediction by SE(3)-equivariant diffusion, sampling 10 Cα conformations in under 6 seconds at 0.45 Å best-of-10 RMSD.
De novo protein design model using flow matching for binder, motif scaffolding, and symmetric generation, with wet-lab-validated binders.
Alignment-free biosynthetic gene cluster detection and annotation from ESM-2 gene embeddings in genomic context, up to 102x faster than antiSMASH.
Kinase-substrate specificity prediction from sequence alone, using ESM-2 embeddings to score phosphorylation across whole mammalian kinomes.
Single-cell foundation model inferring context-specific protein-protein interactions from cancer transcriptomes via a variational graph autoencoder.
Structure-aware protein language model aligning sequence and 3D structure by contrastive learning, with adapter and LoRA fine-tuning tools.
Cryptic protein binding site prediction from sequence, backed by a database of 5,151 cryptic sites mined from 6 million apo-holo PDB alignments.