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Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 649–672 of 1004 filtered models
Graph transformer that scores the accuracy of predicted protein complex structures, ranking model pools using pairwise structural similarity graphs.
Protein question-answering model that fuses sequence and structure into an LLM prompt as virtual tokens, answering free-form questions about function.
Structure-based drug discovery transformer that handles protein-ligand docking and pocket-aware 3D molecule design in one pretrained model.
Allosteric pocket prediction pairing a multitask fine-tuned protein language model with FPocket geometric features, reaching an 89.66% F1 score.
Predicts intrinsic and soft disorder per residue using LoRA adapters on frozen protein language models, released with the SoftDis database.
Enzyme Commission number prediction from protein sequence using four stacked transformer encoders, one per level of the EC hierarchy.
Sparse all-atom denoising models for de novo protein backbone generation, producing designable structures up to 1,000 residues in seconds.
Attention architecture fusing docking scores with protein language model embeddings, so an enzyme gets a different representation per substrate.
Viral capsid fold classifier detecting the jelly roll motif from protein sequence alone, using logistic regression over frozen ProtTrans embeddings.
Protein language model fine-tuned on yeast-display directed evolution data to score rice immune receptor variants for fungal effector binding.
Epitope-conditioned T cell receptor generator that writes its own in-context examples, so receptors can be designed for targets with no known binders.
Sequence-only TM-score prediction pairing frozen ProtT5 embeddings with a bidirectional GRU and multi-scale convolution for protein homology search.
Structure-based drug design model generating 3D ligands inside a protein pocket, aligned by Best-of-K fine-tuning on drug-likeness and docking.
Molecular docking framework that poses several ligands sharing one protein pocket at once, using their consistency to sharpen each prediction.
Epitope prediction model scoring whether a peptide is presented by HLA class I or II, with no allele input needed. Built on ESM-2 embeddings.
Protein function annotation model that parses sequences into residue clusters via community detection on ESM-2 attention, then maps them to GO terms.
Per-residue membrane contact and solvent accessibility prediction from sequence alone, replacing MSA input with language model embeddings.
Protein language model that jointly embeds a set of sequences and reconstructs phylogenetic trees without alignments or guide trees.
Peptide-MHC binding affinity and all-atom 3D structure in one attention network pass, reaching 1.19 Å median C-RMSD at 0.009 s per affinity call.
Cyclic peptide structure prediction for sequences carrying unnatural amino acids, adding atom-level features and cyclization-aware position encoding.
Peptide binder design by mimicking the binding interface of a known receptor or antibody, generating all-atom peptides through latent diffusion.
Antibody CDR sequence-structure co-design by flow matching, starting from an informative structural prior rather than from Gaussian noise.