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Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 1033–1056 of 2565 models
Sequence-based protein-protein interaction predictor over ProtT5 embeddings that reaches 0.70 AUROC on the leakage-free gold standard benchmark.
Flow matching model that builds any non-canonical amino acid into a protein pocket from its SMILES string, at 1.43 Å mean RMSD on held-out ncAAs.
Protein-protein interface prediction from 3D structure using face-centered surface fingerprints and geometric graph attention, at ROC AUC 0.89.
Bacteriophage gene function prediction from genomic synteny, pairing protein language model embeddings with circular attention. AUC above 0.84.
Organic reaction foundation model that tokenizes 3D molecular structure to predict products, retrosynthetic routes, conditions, and yields.
DNA foundation model for germline variant pathogenicity, pretrained on 27 mammalian genomes and fine-tuned on ClinVar and HGMD for SNVs and indels.
Multi-state protein inverse folding model that designs one sequence for two conformations, improving sequence recovery 12% over ProteinMPNN.
Peptide toxicity prediction that fuses frozen ProtT5 residue embeddings with ESMFold-predicted structure in an E(3)-equivariant graph neural network.
Enzyme screening framework pairing a sequence-structure CNN classifier with CLIP-style protein-reaction retrieval to link orphan enzymes to genes.
Structure-based drug design framework pairing pharmacophore-guided latent diffusion with training-free, pocket-aware evolutionary optimization.
Scientific multimodal foundation model, a 241B-parameter MoE with a tokenizer that reads molecular formulas and protein sequences natively.
Contrastive alignment framework that projects H&E histology and single-cell transcriptomic foundation model embeddings into one shared latent space.
Drug perturbation model predicting post-treatment gene expression from a cell's baseline profile and compound structure, zero-shot on unseen drugs.
Enzyme thermostability prediction from sequence, using segment-level attention over ESM-2 embeddings to rank mutation sites for protein engineering.
Drug-drug interaction event text generation from two molecular structures, conditioned on biological functions selected for each drug in the pair.
Multi-modal protein language model using the MSA evolutionary profile as a reasoning step between structure and sequence. 650M outperforms ESM-3 1.4B.
Long-sequence DNA foundation model with groove-aware convolutions and reverse-complement gating over 100kb contexts. Averages 0.708 MCC on GUE.
Gene expression prediction from candidate cis-regulatory elements, fusing DNA sequence, TF binding scores, and epigenomic tracks in a CNN-transformer.
Surface-EMG wristband models that decode hand gestures, handwriting, and wrist movement, generalizing across users without per-person calibration.
Tandem mass spectrum prediction for intact N- and O-glycopeptides that localizes O-glycosylation sites from HCD spectra alone, without ETD.
Protein-ligand binding affinity and mutation ΔΔG predictor fusing residue, ligand, and interaction graphs, evaluated on leak-proof LP-PDBBind splits.
Protein language models trained on billions of natural and synthetic sequences for de novo design and zero-shot mutation-effect prediction.
Whole-genome epigenetic foundation models reading DNA methylation and sequence jointly to detect Alzheimer's and Parkinson's from plasma cfDNA.