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Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 769–792 of 1004 filtered models
Protein-protein interaction prediction from a language model that encodes both sequences jointly, trained on human PPIs and applied across species.
De novo protein backbone design with geometric-algebra attention, sampling designable structures whose secondary structure matches natural proteins.
Cryo-EM foundation model pre-trained on 65 million particle images, enabling zero-shot classification, pose clustering, and quality assessment.
Homology-aware protein language model on a recurrent xLSTM backbone, generating and scoring sequences from long contexts of unaligned homologs.
Protein inverse folding as a generative Markov bridge, refining a structure-derived sequence prior with a frozen protein language model.
Post-translational modification prediction from sequence and 3D structure, quantizing each residue's micro-environment into a per-PTM discrete token.
Peptide-MHC class I immunogenicity prediction fusing sequence, predicted structure, and biochemical properties for vaccine and neoantigen design.
Protein subcellular localization from sequence, returning both a text label and a synthetic fluorescence image of the protein inside a given nucleus.
Biochemistry-aware inverse folding model that augments backbone geometry with physicochemical point clouds, reaching ~90% sequence recovery on CATH.
Estimation of model accuracy for protein complexes, predicting per-residue lDDT from Voronoi contact areas and contact-surface orientation features.
Phase separation prediction from sequence alone, pairing a protein language model with MD-trained conformational features to score every residue.
Protein interface prediction from sequence alone, swapping hand-crafted features for frozen ProtT5-XL embeddings that hold up on remote homologs.
Protein-ligand binding affinity prediction that fine-tunes ESM-2 and ChemBERTa-2 into a shared space where cosine similarity is the predicted pKd.
Inter-residue distance prediction that returns multi-peak distributions, so flexible regions yield several plausible distances instead of one.
Cellular senescence prediction from protein sequence, pairing ESM-2 embeddings with a hybrid BiLSTM-CNN classifier at 86.43% test accuracy.
Protein language model that captures short- and long-range residue co-evolution through a dual pre-training objective, at 3B parameters.
Protein language model that explains single-site mutation effects in natural language and proposes new mutants from free-text instructions.
Long-context protein language model on a bidirectional Mamba backbone, outperforming ESM-2 by up to 30% at matched training token budgets.
Contrastive dual-encoder aligning T-cell receptor CDR3 and peptide epitope sequences in one latent space to rank which receptors bind which antigens.
Lasso peptide language model that adapts ESM-2 to threaded RiPP core sequences, supplying embeddings for cyclase substrate and activity prediction.
Dual-language transformer pretrained on paired protein and mRNA coding sequences, scoring protein and mRNA properties and generating optimized CDS.
Reprograms a frozen single-target diffusion model for dual-target drug design by composing SE(3)-equivariant messages across two aligned pockets.
Peptide representation model that DoRA-tunes ChemBERTa on 100,000 modified and bioactive peptide SMILES for therapeutic property prediction.
Protein sequence design model that identifies each residue from the voxelized atomic microenvironment around it, reaching 68.33% accuracy on TS500.