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Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 745–768 of 2336 models
Single-cell multimodal LLM generating natural-language descriptions of cell type, tissue, disease, and pathway activity from scRNA-seq profiles.
mRNA language model with a hyperbolic prediction head encoding the codon-amino-acid hierarchy, beating Euclidean baselines on 9 of 10 property tasks.
Multi-label classifier over ESM-2 embeddings that separates DNA-binding, RNA-binding, and dual-binding proteins using label-aware attention.
De novo protein backbone generation and sequence-conditioned folding using SE(3) flow matching over a physics-based, clash-free unfolding process.
De novo VHH nanobody binder design that conditions AlphaFold-Multimer with structural templates and language model sequence priors, no retraining.
Cross-species RBP-RNA binding site predictor that turns RNA-binding protein conservation into label smoothing, reaching 0.85 AUC from human to mouse.
Protein solubility mutation-effect predictor built on an anti-symmetric Siamese geometric graph network trained on deep mutational scanning data.
TCR-antigen binding prediction that adapts ESM-2 with LoRA on antigen-specific receptors and fuses the embeddings with a bipartite interaction graph.
Structure-free RNA-small molecule binder discovery model that predicts ligands and their binding sites from RNA sequence using an RNA language model.
Multimodal drug-target interaction model aligning SMILES, molecule text, taxonomy, and protein sequence with a Gramian volume contrastive objective.
Histopathology model predicting homologous recombination deficiency from H&E slides in ovarian cancer, reaching 0.846 AUC and 0.938 specificity.
Spectroscopy-grounded molecular foundation model that reads NMR, IR, and mass spectra as text, elucidating structures and generating 3D conformers.
Peptide aggregation predictor that scores amyloid propensity at single-residue resolution from ESM-2 embeddings, reaching 0.918 AUC on Serrano157.
Multimodal scientific foundation model unifying protein, DNA/RNA, and small-molecule structure in one token vocabulary for cross-domain reasoning.
SE(3)-equivariant chemical language model for pocket-based 3D molecule generation, used to design an HPK1 inhibitor with in vivo anti-tumor efficacy.
Protein-protein interaction predictor fusing evolutionary and structural embeddings to screen bacterial and host-pathogen proteomes in minutes.
De novo antibiotic design framework coupling a 6.4B-parameter protein language model with reinforcement learning to generate antimicrobial peptides.
Hierarchical transformer for virus discovery in metagenomes, classifying viral genomes across taxonomic ranks and flagging candidate novel lineages.
Chemical language model for fragment-based drug discovery, trained on all 62M ZINC-22 fragments. Samples 99.9% chemically valid fragment SMILES.
Protein structure prediction from general-purpose transformer blocks and flow matching, with no MSAs, pair representations, or triangle attention.
Predicts virtual single-cell spatial transcriptomics from H&E histology using frozen pathology foundation models and spot-level supervision.
Splice donor and acceptor site prediction from raw DNA, scoring every position of a 20 kb window with an ensemble of dilated residual CNNs.
Phylogeny-aware genomic language model scoring variant effects from whole-genome alignments and species trees across three evolutionary timescales.