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Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 865–888 of 2336 models
RNA language model transfer-trained from ESM-2 via a pseudo-protein alphabet mapping, outperforming 12 RNA language models in zero-shot evaluation.
Multi-sequence MRI foundation model pretrained on 336,476 volumetric scans, ranking first on 41 of 44 downstream clinical benchmarks.
Model quality assessment network predicting per-residue lDDT, CAD-score, and RMSD for protein loops in predicted and designed structures.
Single-cell perturbation prediction by conditional flow matching, using one cell-type-conditioned model in place of a separate model per cell type.
Brain MRI model for noninvasive IDH genotyping of glioma, adapting a pretrained SWIN-UNETR backbone to reach 90.6% AUC on an external cohort.
Gram-negative bacterial effector prediction refining frozen ESM-1b embeddings with a mixture of convolutional experts and a transformer.
RNA foundation model pretrained jointly on sequences and secondary structures for structure prediction, homology and splice site classification.
Blind flexible protein-ligand docking model trained by two-player self-play, predicting bound ligand and pocket poses in 0.32 seconds per complex.
Generative diffusion transformer for protein-ligand dynamics that produces trajectories, inpaints missing ligand atoms, and samples transition paths.
GPCR ligand bioactivity predictor combining ProteinBERT receptor embeddings with molecular descriptors, spanning the class A receptor family.
Chest CT masked autoencoder pretrained on over 5,000 volumes, fine-tuned to classify interstitial lung disease under Fleischner Society criteria.
Multi-organ CT registration model that aligns thorax, abdomen, and pelvis in one pass and transfers to unseen datasets without fine-tuning.
Amyloidogenicity predictor that classifies hexapeptides and scans whole proteins for aggregation-prone regions using frozen ESM-2 embeddings.
Single-cell multi-omics foundation model whose three-stage pretraining and distillation yield RNA-and-ATAC-aware embeddings from RNA-only input.
Multimodal, retrieval-augmented protein foundation model that learns family-specific evolutionary constraints with optional structure conditioning.
Molecular structure elucidation model that reads IR, Raman, UV-Vis, NMR, and mass spectra as text and generates SMILES end to end.
Molecular reasoning language model for molecule captioning and text-to-molecule generation, trained by chain-of-thought distillation then reward RL.
Histopathology segmentation model aligning SAM to clinical intent through direct preference optimization, tested zero-shot on 12 external datasets.
Structure-based virtual screening model that jointly predicts protein-ligand complex structures and binding fitness from sequence and SMILES.
Biomedical named entity recognition transformers, with task-specialized checkpoints for chemicals, diseases, genes, proteins, species, and anatomy.
Protein-ligand interaction model pretrained on solvent-aware conformer ensembles, reaching 97.1% AUC on DUD-E virtual screening.
MSA-based protein language model for unsupervised contact prediction, outperforming ESM2-15B with 111M parameters and leading on interface contacts.
Binding free energy change (ΔΔG) predictor for protein-protein interfaces, decomposing mutational effects into inverse-folding and energy-model terms.
Protein surface tokenizer that turns surface-exposed residues into codebook tokens, lifting SKEMPI binding affinity change prediction to r = 0.600.